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H: How to model a Bimodal distribution of target variable
I want to regress on this target, have tried multiple transformations to bring it to normal but its not helping, read some stuffs online but none of the suggestions have worked till now.
I am attaching the residual histogram as well, somehow the residuals are ... |
H: Non-mutal exclusive classification task examples
I am reading the excellent Hands-on Machine Learning with Scikit-Learn and TensorFlow and in chapter 10, the author says:
"For the output layer, the softmax activation function is generally a
good choice for classification tasks (when the classes are mutually
ex... |
H: LSTM text generation
Most of the examples I have found online for LSTMs refer to "random" text generation.
One of the problems that I'm trying to solve is to generate a "summary" of many docs into 1 doc. For example:
News Article: Barack Obama life history (2K words)
Wikipedia: Barack Obama (10K words)
Barack Ob... |
H: python: Are there are some class like Voting classifier for three or four regression model
I want to ensemble three or four regression model: like GBDT, XGBDT, SVM. I know there are votingC = VotingClassifier() for classifier. I want to know are there some methods or function for ensemble regression model. Now, I j... |
H: How to restore deleted objects in R?
Suppose if I delete all the objects from current session:
rm(list=ls())
Is there any way in base R or using a function from a package which lets me restore the deleted objects from the current session?
AI: The answer is unfortunately no. There is no handy ctrl-z method.
A tip ... |
H: What exactly means CNN is position equivariant
There is quite a good explanation which fully comply with my vision. But seems it lacks one final step. As Jean states, moving an object significantly in the input image will cause the change in which neuron is activated in the yellow layer (the one previous to the fir... |
H: How to distort data in a clever way?
For example, I have some time series. How can I change my data, so it will not be obvious to understand what was original values?
Ideally transformation would allow to revert and reconstruct original data with some noise(or to save the relationship between time series values wi... |
H: An Artificial Neural Network (ANN) with an arbitrary number of inputs and outputs
I would like to use ANNs for my problem, but the issue is my inputs and outputs node numbers are not fixed.
I did some google searches before asking my question and found that the RNN may help me with my problem. But, all examples whi... |
H: Keras: visualizing the output of an intermediate layer
I have read the docs here and I understand the general idea. I am able to visualize the weights of the intermediate layers. However, I'm having trouble visualize the activations. Here's what I have:
I trained my model and saved the weights in a file called weig... |
H: Recurrent neural network producing same predictions
I am trying to train a recurrent neural network that I built in keras on timeseries data to predict number of sales for next 10 days. For this, I've created my dataset as -
var(t) -> var(t+1)
var(t+1) -> var(t+2)
var(t+2) -> var(t+3)
var(t+3) -> var(t+4) and so on... |
H: Notion of cluster centers and cluster comparison in Density Based Algorithms
I have done some research on clustering algorithms since for my goal is to cluster noisy data and identify outliers or small clusters as anomalies. I consider my data noisy because of my main feautures can have quite varying values. Theref... |
H: Multidimensional regression in Keras
I'm trying to implement the One Hidden Layer Model presented in this article using Keras.
This is my code:
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten, Activation
from keras import optimizers
model = Sequential()
model.add(Dense(100, inp... |
H: TensorFlow - Resume training in middle of an epoch?
I have a general question regarding TensorFlow's saver function.
The saver class allows us to save a session via:
saver.save(sess, "checkpoints.ckpt")
And allows us to restore the session:
saver.restore(sess, tf.train.latest_checkpoint("checkpoints.ckpt"))
Insi... |
H: How do I forecast sales data down to the individual item?
I have a dataset that looks like,
order datetime, customer id, product name, type of product, quantity sold
I want a model to forecast sales for each individual item. I'm thinking of using one of the following but would like some advice, literature, or oth... |
H: Identfying spikes in data
I am a little new at this - I am used to just querying data and not so much analysis of the data so any help would be greatly appreciated.
I have some data that is trending month over month. Some months with an increase in volume and others with a decrease. The goal is to identify a "spike... |
H: Using GridSearchCV for custom kernel SVM in scikit-learn
I would like to use scikit-learn's GridSearchCV() to do a grid search on custom parameters in a kernel I have specified. Specifically, the kernel is of the form
SeqKernel(x, y, orig_kernel, cut_off, order)
Here, orig_kernel is a kernel typically used in SVM ... |
H: Why Decision Tree boundary forms a square shape and SVM a circular/oval one?
I was going through a Udacity tutorial wherein a few data points were given and the exercise was to test which of the following models best fit the data: linear regression, decision tree, or SVM. Using sklearn, I was able to determine that... |
H: What is deconvolution operation used in Fully Convolutional Neural Networks?
When I was reading this this paper, Fully Convolutional Networks for Semantic Segmentation, I found that they use an up-sampling layer to classify each pixel in to a class. I have two questions:
How do you understand the mathematics behin... |
H: Sorting bar chart in Tableau by one category of bars
I have a bar chart that looks like this (truncated for space, orange label obscured for privacy):
Right now, it is ordered by US state. The color distinction is for something called "Entity".
Here are the set ups for Marks, Columns, and Rows, and the legend:
W... |
H: Handling large imbalanced data set
I have an imbalanced data set consisting of some 10's of millions text strings, each with thousands of features created by uni- and bigrams, and additionally I have also the string length and entropy of string as features.
It is a multiclass data set (40-50 classes), but it is im... |
H: Concatenate dataframes Pandas
I have three dataframes. Their shapes are (2656, 246), (2656, 2412) and (2656, 7025). I want to merge dataframes as above:
So It will result a (2656, 9683) Dataframe. Thanks for any help.
Typo on image: on Dataframe 3, it will 7025, not 5668.
AI: Assuming that the rows are in same ord... |
H: SGD data should be randomly selected or sequentially feed?
When training neural network, is it better to randomly choose data for every batch or feed the data sequentially? Why?
AI: If you feed the data randomly, there are fewer chances of overfitting than if you feed the data sequentially.
If the data is fed seque... |
H: Why is duplicating inputs bad?
I am trying to predict an output value based on several continuously-valued inputs using a regression model.
I am not sure what approach is appropriate to scale/transform the input data for the regression. Let's just pretend that it is unlabeled data.
My most naive approach would be t... |
H: Importing Common Constants to R and Python
I use Python for data munging, R for data analysis, and I combine both by running the munging/analysis sequentially in a Makefile. My Python and R scripts depend on various constants. I typically store my Python constants in a settings.py file, and I import this file acros... |
H: Image Feature Vectors
I have downloaded a dataset from Amazon. http://jmcauley.ucsd.edu/data/amazon/ Dataset involves feature vectors of images. There are around 1.5 M feature vectors.
Dataset consists of 10 characters (the product ID), followed by 4096 floats (repeated for every product).
Every product image invo... |
H: Prepending Input layer to pre-trained model
I'm trying to input numpy arrays of shape (1036800,) - originally images of shape (480, 720, 3) - into a pre-trained VGG16 model to predict continuous values.
I've tried several variations of the code below:
input = Input(shape=(1036800,), name='image_input')
initial_mode... |
H: Why do convolutional networks work so well for images?
Convolutional artificial neural networks work well in particular with images. Why?
AI: The convolution neural networks take into consideration that an image already has a two-dimensional structure. This is a domain knowledge provided by humans and not something... |
H: What does a Word2Vec represents?
Does a single word vector, trained using Word2Vec or a similar approach, carries information or meaning?
AI: So we have that a word to vector model has been trained on a certain corpus to be able given words as inputs (one hot encoding is one way for the input) to represent the word... |
H: What are the disadvantages of using deep neural networks compared to a linear model?
We have heard a lot about the advantages that artificial neural networks have over other models but what are the disadvantages of them in comparison to the simplest case of a linear model?
AI: First of all, we should say that a sin... |
H: What do the hidden layers of a neural network try to learn?
Typically all the layers of an artificial neural network are trainable. But what are the hidden layers trying to learn?
AI: Each hidden layer represents a nonlinear application of a function on the inputs of the previous layer.
The first layers perform a f... |
H: What are the advantages of the rectified linear (relu) over the sigmoid activation function in networks with many layers?
The state of the art of nonlinearity is to use rectified linear units (ReLU) instead of a sigmoid function in deep neural networks. What are the advantages?
AI: The sigmoid function becomes asym... |
H: Data not consistent
I have data set of client profile and mutual funds , now the problem is there is huge numbers of different mutual funds available and based on history I can see for certain type of client profile more than 20 different funds have been suggested ?
Now I have no idea which algorithm should I use t... |
H: Why Orange "Predictions" and "Test & Score" produce different results on the same data?
It is not very clear what is the difference between the following two schemes:
From help docs:
Test & Score widget: tests learning algorithms on data.
Predictions widget: shows models’ predictions on the data. Which model? Pre... |
H: What is the purpose of the discriminator in an adversarial autoencoder?
This is specific to the generative adversarial network (GAN) proposed in A. Makhzani et al. "Adversarial Autoencoders". In a traditional GAN, the discriminator is trained to distinguish real samples in $p(x)$ from fake generated samples output ... |
H: How to use boolean data in DecisionTreeClassifier in sklearn?
I am trying to build a decision tree using python and sklearn DecisionTreeClassifier.
One of the data_type used for splitting the tree is Boolean(let it be x).However the tree that is generated contains comparisons like x<=0.5 .
This does not make sens... |
H: Dataset - Sample pdfs for text processing?
I'm looking for a rather large amount of pdf files for testing my text processing program. Tried looking for an open site to get like some thousand pdfs, but wasn't able to find anything. I don't really know if that is the right place to ask (probably not) but maybe one ha... |
H: How can I do tree_method ='exact' in XGBoost classifier?
I am doing XGBoost classification on a huge data set and its showing:
Tree method is automatically selected to be 'approx' for faster speed. to use old behavior(exact greedy algorithm on single machine), set tree_method to 'exact'
How can I shift it to be exa... |
H: What are the inputs to a logistic regression? Probability or trial result?
It is a very basic question, but cannot find a satisfactory answer to. When we do logistic regression, what are the inputs? Suppose we have a dataset of students giving number of hours each student spent studying, and the end result of wheth... |
H: ML project ideas for dataset
Not sure if this is the right forum, but currently i have a dataset which contains a list of TV shows. Each record contains pricing between competitors (price in provider 1. Example: Itunes) TV show cover image, synopsis, country of origin, language, etc. Looking for ideas what project ... |
H: python print values seasonal_decomposition
I am totally beginner in Python and after using seasonal_decompose for time series decomposition result=seasonal_decompose(series, model='additive', freq=365) I got plotted results with commands result.plot() and pyplot.show(), but I cannot understand how to print this res... |
H: Difference between segmentation and effect of explanatory variables
In the context of discrete choice models, what difference does it make in segmenting my sample based on a particular "criteria" and study the effects of explanatory variables on each segment VERSUS Just adding the "criteria" as another explanatory ... |
H: How to evaluate the performance based on rate data
I have the following data:
Goal Achieved
100 90
150 130
200 175
...
The first column "Goal" is the number which should be done that day, and the column "Achieved" is the number that was actually done that day. Each row stands for a day... |
H: How to handle missing data for machine learning
I'm trying to come up with a data structure to predict water visibility in a lake. I have some measured samples but would like to take other features into the equation.
As an example, I would like to get weather data such as rain and temperature for the past 7 days of... |
H: Categorize observations with inconsistent text descriptions
Given data table with inconsistent item descriptions, how could I most effectively assign an item category using R (i.e. dplyr), MySQL, or Python? An R based solution is preferred.
MySQL is the data source. As is, case-when logic assigns an item category b... |
H: validation/test set uniqueness question
Hopefully a simple question, but it's a little unclear to me on how best to separate train/validate/test sets.
I have say 100 examples of class A. I'm classifying text into either class A, which I care about, or class B, which could be any text in the world (negative class).... |
H: How to precompute one sequence in a sequence-pair task when using BERT?
BERT uses separator tokens ([SEP]) to input two sequences for a sequence-pair task. If I understand the BERT architecture correctly, attention is applied to all inputs thus coupling the two sequences right from the start.
Now, consider a sequen... |
H: Visualizing effect of regularization for linear regression problem
I wanted to put together an example notebook to demonstrate how regularization makes an impact for such a simple model as a simple linear regression. When executing the below script though, I notice that the LinearRegression() and Ridge() models bot... |
H: How to count the number of rows by variable in R
Context: I am trying to determine a way to create an extra step in between my dataset and the code below or optimise the code altogether. Currently, the data frame "df_b" looks as follows. In column 4, the repetitions exceed 1 (as they denote the number of times a w... |
H: How to improve the learning rate of an MLP for regression when tanh is used with the Adam solver as an activation function?
I'm trying to use an MLP to approximate a smooth function f : R^3 -> R, that takes a point in space as an argument, and returns a scalar value.
The MLP architecture has a 3-dimensional (for 3 ... |
H: How to control a decision tree?
This is my R script for a decision tree:
library(caret)
library(rpart.plot)
library(plyr)
library(dplyr)
library(rpart)
data("iris")
names(iris) = tolower(names(iris))
table(iris$species)
suppressMessages(library(caret))
ind... |
H: Beginning my data science journey
I am a Master's student in physics. Lately I have been intrigued by the field of data science. I have beginner level knowledge of python, undergraduate level knowledge of mathematics and master's level knowledge of physics. I now want to learn data science. I scoured the internet b... |
H: Why do I get different results at inference time even with fixed seed?
I am a very beginner in deep learning and am playing with voice cloning project. I trained my dataset and used the trained model to synthesize some sentences and was surprised to get a very different output each time I ran the synthesis (output ... |
H: Persistence and stationarity together
I am trying to analyse a time series. I want to get only quantitative results (so, I'm excluding things like "looking at this plot we can note..." or "as you can see in the chart ...").
In my job, I analyse stationarity and persistence. First, I run ADF test and get "stationary... |
H: How to improve language model ex: BERT on unseen text in training?
I am using pre-trained language model for binary classification. I fine-tune the model by training on data my downstream task. The results are good almost 98% F-measure.
However, when I remove a specific similar sentence from the training data and a... |
H: Error: `raise ValueError( ValueError: Missing column provided to 'parse_dates': 'Date'
I am using a .csv with two columns. The first has dates and the second has temperatures. I would like to plot it with dates on the x-axis and temperatures on the y-axis.
I used this command:
dataset = pandas.read_csv('/home/Ubunt... |
H: Calculating statistical ranks between datasets with unpaired observations
The problem is the following:
I have multiple datasets for which I want to calculate a ranking for each. All observations contained in the datasets can be arbitrarily permuted, so they are unpaired, to speak in the words of statisticians.
Exa... |
H: Applied and view jobs ratio
I have the following data set where the column "kind" can be V(view) or A(apply), how can I do the following things given a particular job id how many applicant Apply (A) to that particular job and how many applicant View(V) the particular job? So I want a column with job and two colum... |
H: How can I change shape of the input image array as per my trained TensorFlow model input?
I have a Tensorflow model weight file that I am using to make the prediction on test images. These test images are in NumPy array format and the shapes of the images are (720, 1280, 3).
I am getting the following error while m... |
H: Can I leave natural outliers in a dataset in training?
Can I leave unedited natural outliers in a dataset (outliers that have not appeared just because of mistyping of mistakes in the data)? Or should I also remove them or change them?
AI: Yes you should keep the natural outliers in a dataset. They represent an ext... |
H: Print histogram for each of the columns in my table with one single command
I would like to draw a histogram for each of the columns in my data.frame without having to write the the names of all of them, similar to what I did for inspect their unique values with:
sapply(data, unique)
So I tried
sapply(data, hist)
... |
H: Should I merge multiple target bins into one for better results?
I have a multiclass classification task where the target has 11 different classes. The target to classify is the Length of Stay in a hospital and the target classes are in different bins, for example, 1-10, 11-20, 21-30 and so. So far I have tried Neu... |
H: Clustering text data based on sentiment?
I am scraping reviews off Amazon with the intent to perform sentiment analysis to classify them into positve, negative and neutral. Now the data I would get would be text and unlabeled.
My approach to this problem would be as following:-
1.) Label the data using clustering a... |
H: Why not rule-based semantic role labelling?
I have recently found some interest in automatic semantic role labelling. Most introductory texts (e.g. Jurafsky and Martin, 2008) present approaches based on supervised machine learning, often using FrameNet (Baker et al. 1998) and PropBank (Kingsbury & Palmer, 2002). In... |
H: Change line type in gpplot in R
Context: I have two variables under emotion_dict that I am graphing in the same line graph.
Problem: However when I change the linetype in geom_line, it changes the appearance of both variables.
Question: Does anyone know how to alter the code below to keep the line types separate an... |
H: How to plot the sum of something over an interval of time?
Say I have a dataframe with date as index. I would like to plot a line plot of some values in a column A over a given time frame. Say for the month of August. In column A I have several entries for example for the 02/08/2020 and a four different values on 0... |
H: Choose ROC/AUC vs. precision/recall curve?
I am trying to get a clear understanding on various classification metrics, including knowing when to choose ROC/AUC as opposed to opting for the Precision/Recall curve.
I am reading Aurélien Géron's Hands-On Machine Learning with Scikit-Learn and TensorFlow book (page 92)... |
H: Document Content
I have a set of .pdf/.docx documents with content. I need to search for the most suitable document according to a particular sentence. For instance:
Sentence: "Security in the work environment"
The system should return the most appropriate document which contains at least the content expressed in... |
H: Massive difference in accuracy of KNN depending on random_state
pardon the noob question but I am baffled by the following behavior. My model has MASSIVELY different results based on the random seed. I want to train a KNN classifier on the famous Kaggle Titanic problem where we attempt to predict survival or not. I... |
H: How to feed a Knowledge Base into Language Models?
I’m a CS undergrad trying to make my way into NLP Research. For some time, I have been wanting to incorporate "everyday commonsense reasoning" within the existing state-of-the-art Language Models; i.e. to make their generated output more reasonable and in coherence... |
H: Extracting the metadata form Json file making it columns
I have the following json data file which I have converted to pandas dataframe. The columns are as follows
Index(['id', 'title', 'abstract', 'content', 'metadata'], dtype='object')
I am particularly interested in the column 'metadata' an element of the colum... |
H: should text augmentation take place before or after splitting the dataset?
I've a text dataset with ~20000 samples (which is not enough).
I used text augmentation to "invent" more samples so essentially I've multiplied each sample by 10 - ending up with ~200000 samples (each of the 10 is a different kind of augment... |
H: The behavior of the cross validation error and training error in underfitting case is not clear
I currently study the "Machine Learning" course on Coursera.org by Andrew Ng, it comes to a topic that discusses the performance of learning algorithms under different conditions.
Here, we discuss the case when the algor... |
H: For a student who is a beginner in quantitative research and statistics, which is the better statistical tool to start: R or IBM SPSS? Why?
Currently, I am writing my research design. However, I am still indecisive on what statistical tool should I use for the data analysis. I tried looking up on the internet and t... |
H: How could I estimate slope of lines on a scatter plot?
I have a list of coordinate pairs. To the human eye, they form lines with a constant slope:
This is how I generated that image above:
import numpy as np
np.random.seed(42)
slope = 1.2 # all lines have the same slope
offsets = np.arange(10) # we will have 10 ... |
H: Could I use some elements of my target variable to predict it?
I'm trying to predict if a company will bankrupt, I use a dataset of 2020 and I manually created my target variable with the status of the company the status date, status reason to create my target variable.
Could I use these variables too for my model ... |
H: Trouble understanding regression line learned by SGDRegressor
I am working on a demonstration notebook to better understand online (incremental) learning. I read in sklearn documentation that the number of regression models that support online learning via the partial_fit() method is fairly limited: only SGDRegress... |
H: Labels in SVM algorithm
I am reading some ML books (Burkov's and Raschka's), and i have seen there, that for a binary classification problem using SVM, my "positive" label needs to be equal +1 and my "negative" label needs to be -1.
My dataset has labels equals to +1 and 0. Should i change all the 0 to -1? Or let's... |
H: Difference between prototype and centroid
Are these two terms "prototype" and "centroid" exchangeable? I know prototypes can be calculated using the mean of the features. Is it the same for centroid?
AI: No, they are not exchangeable.
Centroid refers to "the arithmetic mean position of all the points in the figure"... |
H: How to combine preprocessor/estimator selection with hyperparameter tuning using sklearn pipelines?
I'm aware of how to use sklearn.pipeline.Pipeline() for simple and slightly more complicated use cases alike. I know how to set up pipelines for homogeneous as well as heterogeneous data, in the latter case making us... |
H: Mapping values in Logistic Regression
When mapping probabilities obtained in logistic regression to 0s & 1s using the sigmoid function, we use a threshold value of 0.5. If the predicted probability lies above 0.5, then it gets mapped to 1, if the predicted probability lies below 0.5, it gets mapped to 0. What if th... |
H: Categorical to One hot encoding - Big data
I have a sales dataset which consists of binary label as output - "Business win" and "Business loss" of our products.
We have a set of 1st level customers (lets call that group as jacks) with whom we do we business. These jacks then sell our products to end customers (let'... |
H: How to make a model suffer from underfitting
I would like to show an example of my model when it is overfitting, and when it is underfitting. Now overfitting is pretty straight forward, just train on small data, and the model will remember the data. But how do I show example of underfitting? I have a couple of sugg... |
H: Logistic Regression mapping formula
Sigmoid function predicts the probability value which is between 0 & 1. What is the formula in logistic regression that maps the predicted probabilities to either 1 or 0?
AI: You get the output of the logistic regression $\sigma$, which is between $0$ and $1$.
Default option (is ... |
H: How to perform regression on image data using Tensorflow?
Overview
I understand the surface of the mathematics* of simple neural networks. I went through single-label image classification problems (ie using MNIST & fashion-MNIST datasets) using the native tensorflow, performed multi-label image classification using... |
H: How does Keras Tokenizer choose tokens given a sentence?
I tried to find the answer to this question but I can't find anything, so I ask here: How does Keras Tokenizer choose tokens given a sentence of words ?
To be more precise with what I want to know, given this simple example:
#Import module
from keras.preproce... |
H: Custom vectorizer transformer in sklearn with cross validation
I created a custom transformer class called Vectorizer() that inherits from sklearn's BaseEstimator and TransformerMixin classes. The purpose of this class is to provide vectorizer-specific hyperparameters (e.g.: ngram_range, vectorizer type: CountVecto... |
H: Data snooping and information leakage?
I need help in deciding whether my below implementation imposes data snooping bias and information leakage from the test/evaluation set to the train set.
I have a text corpus of 10k+ short online comments. Many have special symbols and emojis. These might theoretically be hand... |
H: No module named 'model'
I am trying to use the CoAtNet class in the following link
CoAtNet Class from Github
but I always have error while I am running the following lines:
from torch import nn, sqrt
import torch
import sys
from math import sqrt
#sys.path.append('.')
from model.conv.MBConv import MBConvBlock
from m... |
H: Recommended number of features for regression problem
In the following link the answer recommends a feauture amount of N/3 for regression (or it is quoted).
Where N corresponds to the sample size:
How many features to sample using Random Forests
Is there any paper which quotes this?
AI: Not sure what is meant by a ... |
H: Error in assign a numeric value
I would like to transform a string into a number. This is my code:
test <- starwars
home <- test$homeworld
home <- as.numeric(home)
but I have this error:
Error: 'list' object cannot be coerced to type 'double'
My goal is to assign a number to every homeworld. Obviously the lines w... |
H: Knit with R markdown
I have tried running some code on RStudio Desktop, within the Chunk the codes runs smoothly, but when knitting to view as html, I get the message that something is wrong with a line of code. What can I do please.
[This is the code I wrote and I was okay][1]
But I got this error message while tr... |
H: Changing the predicted variable from price to price/km due to better visual correlation
I'm working on a dataset of Uber Rides from Kaggle. Of the important variables there are pickup and drop-off coordinates, passenger count, datetime of pickup, distance and the final price. I'm currently in the exploration phase ... |
H: Hidden Markov Models: Best practices in selecting observable variables
I am just getting started with Hidden Markov Models. In selecting my observable variables, there are some where I believe the recent change in the variable is potentially more predictive than its level. For example, in finance, the level of of a... |
H: Binary classification with seperate training and testing datasets
I have two datasets (train.csv) and (test.csv) revolving around predicting the death outcome for a disease. Both sets include 20 independent variables (age, weight, etc), but only the train.csv dataset contains the true death outcome (0 for alive, 1 ... |
H: How to draw a density plot?
This is my R script to draw the density plot:
df <- iris
plot(density(df$Sepal.Length), main="Density Plot", ylab="Frequency", sub=paste("Skewness:", round(e1071::skewness(df$Sepal.Length), 2)))
Is there a way to plot three density plots (one for every species: setosa, virginica and ver... |
H: ValueError: Negative dimension size caused by subtracting 5 from 3
I get this error
ValueError: Negative dimension size caused by subtracting 5 from 3 for '{{node conv2d_77/Conv2D}} = Conv2D[T=DT_FLOAT, data_format="NCHW", dilations=[1, 1, 1, 1], explicit_paddings=[], padding="VALID", strides=[1, 1, 1, 1], use_cudn... |
H: Specificity over 100
I am construction a deep neural network for a classification task, when I look at the metrics, I have a specificity of 1.04. Is it possible to have this metric over 100 ? How do you interpret it?
Thank you.
AI: The specificity is defined as
$Specificity = \frac{\sum{True Negative} }{\sum{True N... |
H: Logistic regression - Odds ratio vs Probability
In Logistic regression, the final values we achieve are associated with Probability. Then why do we need Logit/Log of odds? We can directly use probability.
Is Logit used to get the equation of a best fit line?
AI: The Log of Odds is used for interpretation purposes i... |
H: Keras: How to restore initial weights when using EarlyStopping
Using Keras, I setup EarlyStoping like this:
EarlyStopping(monitor='val_loss', min_delta=0, patience=100, verbose=0, mode='min', restore_best_weights=True)
When I train it behaves almost as advertised. However, I am initializing my model weights before... |
H: Logistic Regression - Odds & log of odds
ln(p1−p)=β0+β1X
The equation of line in the above equation denotes that the log of odds is linearly related to the predictor variables.
Why is log of odds linearly related to the predictor variables, but not the plain odds?
AI: For understanding this first we will have to lo... |
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