text stringlengths 83 79.5k |
|---|
H: Sampling Technique for mixed data type
I am looking for a very specific sampling technique which pertains to a very large dataset with mixed data type i.e, I have categorical as well as continous variables and want to have a sample that represents the population of such kind of data as closely as possible. It would... |
H: How do you add negative class sample for binary classification?
How do you prepare the negative dataset for binary classification? Let us say that I am building a classifier that has to classify whether the input image is of a car or not. I already have a dataset that consists of thousands of cars. But what about n... |
H: Why keras Conv2D makes convolution over volume?
I have a very basic question, but I couldn't get the idea about 2D convolution in Keras.
If I would create a model like this :
model = tf.keras.Sequential([tf.keras.layers.ZeroPadding2D(padding=(3,3), input_shape=(64,64,3)),
tf.keras.layer... |
H: What is the difference between a test with assumption of standard normal distribution and t-test? And when to use each one?
I am studying statistics on my own and I am not understanding when to use a one-sample t-test or a test with assuming a standard normal distribution. As I understand, both are comparing a popu... |
H: Boosting algorithms only built with decision trees? why?
My understanding of boosting is just training models sequentially and learning from its previous mistakes.
Can boosting algorithms be built with bunch of logistic regression? or logistic regression + decision trees?
If yes, I would like to know some papers or... |
H: What backpropagation actually is?
I have a conceptual question due to terminology that bothers me.
Is backpropagation algorithm a neural network training algorithm or is it just a recursive algorithm in order to calculate a Jacobian for a neural network? Then this Jacobian will be used as part of the main training ... |
H: Normalization with learning/test dataset in [0,1]
Say you split your data into two sets: training and test sets. You know that the inputs of your data are in [lower_bounds, upper_bounds]. Now, assume that you would like to do a min-max normalization on your inputs between $[0, 1]$. For the values of the max and the... |
H: Cosine similarity between sentence embeddings is always positive
I have a list of documents and I am looking for a) duplicates; b) documents that are very similar. To do so, I proceed as follows:
Embed the documents using paraphrase-xlm-r-multilingual-v1.
Calculate the cosine similarity between the vector embeddin... |
H: How to visualize a hierarchical clustering as a tree of labelled nodes in Python?
The chapter "Normalized Information Distance", visualizes a hierarchical clustering as a tree of nodes with labels:
Unfortunately I cannot find out how to replicate this visualization, maybe they did it in a manual way with Tikz?
How... |
H: Excluding data via confidence score: Is it a good idea?
Let's say I have a model which has a binary classification task (Two classes of 0 and 1) and therefore, it outputs a number between 0 and 1, if it is greater than 0.5 we consider it to be class 1 and 0 the other way around.
Now let's say we remove any results ... |
H: What are the possible applications of a Data Scientist in the design fase of an Aerospace Or Railway Engineering industry?
I have been trying to understand this for a long time, but this information proves to be incredibly elusive online.
What are possible jobs that a pure Data Scientist, without much background kn... |
H: Calculating the dissimilarity between term frequency vectors
Given that a document is an object represented by what is called a term frequency vector. How can we calculate the dissimilarity between term frequency vectors?
AI: There are several ways to find the relationship between vector representations in NLP, suc... |
H: How create a representative small subset from a huge dataset, for local development?
I have a time series problem and the dataset I'm using is rather huge. Around 100GB. For local development I'm trying to subset this into a very small batch around 50MB, just to make sure unit tests and some very streamlined "ana... |
H: How to fix my CSV files? (ValueError: Found array with 0 sample(s) (shape=(0, 1)) while a minimum of 1 is required)
I have tried to import two csv files into df1 and df2. Concatenated them to make df3. I tried to call the mutual_info_regression on them but I am getting a value error ValueError: Found array with 0 ... |
H: Cross-validation split for modelling data with timeseries behavior
Background: I have a dataset that is generated every month (it is similar with card data that contains card demography and transactions every month and new accounts can be added in the middle of data series). From those historical data, I need to bu... |
H: RANSAC and R2, why the r2 score is negative?
I was experimenting with curve_fit, RANSAC and stuff trying to learn the basics and there is one thing I don´t understand.
Why is R2 score negative here?
import numpy as np
import warnings
import matplotlib.pyplot as plt
from sklearn.metrics import r2_score
from sklearn... |
H: How can word2vec or BERT be used for previously unseen words
Is there any way to modify word2vec or BERT to extend finding out embeddings for words that were not in the training data? My data is extremely domain-specific and I don't really expect pre-trained models to work very well. I also don't have access to hug... |
H: How to get best data split from cross validation
I have trained a Random forest regressor which is giving me a rmse score of 70.72. But when I tried the same model in cross_val_score with a cv of 10, it gave me an array that looks something like this.
array([63.96728974, 60.43972474, 63.98455253, 61.69770344, 94.24... |
H: Does hyperparameter tuning of Decision Tree then use it in Adaboost individually vs Simultaneously yield the same results?
So, my predicament here is as follows, I performed hyperparameter tuning on a standalone Decision Tree classifier, and I got the best results, now comes the turn of Standalone Adaboost, but her... |
H: Scikit-learn's implementation of AdaBoost
I am trying to implement the AdaBoost algorithm in pure Python (or using NumPy if necessary).
I loop over all weak classifiers (in this case, decision stumps), then overall features, and then over all possible values of the feature to see which one divides the dataset bette... |
H: For sklearn ML algorithms, is it possible to use boolean data alongside continuous data for the predictive data, and if so how can the data be scaled?
I have a medium size data set (7K) of patient age, sex, and pre-existing conditions. Age of course is from 0-101, sex is 1 for male, 2 for female, and -1 for diverse... |
H: Understanding SVM mathematics
I was referring SVM section of Andrew Ng's course notes for Stanford CS229 Machine Learning course. On pages 14 and 15, he says:
Consider the picture below:
How can we find the value of $\gamma^{(i)}$? Well, $w/\Vert w\Vert$ is a unit-length vector
pointing in the same direction as $... |
H: Understanding Lagrangian for SVM
I was referring SVM section of Andrew Ng's course notes for Stanford CS229 Machine Learning course. On page 22, he says:
Lagrangian for optimization problem:
$$\mathcal{L}(w,b,\alpha)=\frac{1}{2}\Vert w\Vert^2-\sum_{i=1}^n \alpha_i[y^{(i)}(w^Tx^{(i)}+b)-1] \quad\quad\quad \text{...... |
H: OneVsRest Classification why do the probabilites sum to 1?
I am using OneVsRest Classifier in sklearn. So a multilabel model, 4 models for each class (i have 4 classes). When i called the predict_proba method i therefore get an array with 4 columns each one corresponding to a probability for that class. e.g.
0 ... |
H: Comparison of classifier confusion matrices
I tried implementing Logistic regression, Linear Discriminant Analysis and KNN for the smarket dataset provided in "An Introduction to Statistical Learning" in python.
Logistic Regression and LDA was pretty straight forward in terms of implementation. Here are the confusi... |
H: How to write a Proof-Of-Concept(POC) for machine learning model?
I've found that If any company is interested in your product, But they don't know it will fit, it will work or they don't trust you, They will ask you for a POC or Proof-Of-concept
I need to write a Proof-Of-Concept(POC) for my machine learning develo... |
H: how is validator created in python and what are most popular libraries / modules to learn first
I have a df which has a serial number generated with each new record. The serial number combines with some other part like state code, year of registration and category code. So it has a format like below:
| DOR | App... |
H: Binary document classification using keywords for a very small dataset
I have a set of 150 documents with their assigned binary class. I also have 1000 unlabeled documents. Each document is about the length of a journal paper. Each class has 15 associated keywords.
I want to be able to predict the assigned class of... |
H: Can a CNN have a different number of convolutional layers and kernel and what does it mean?
So if I have $3$ RGB channels, $6$ convolutional layers and $4$ kernels, does this mean that each kernel does a convolution on each channel and so the input for the next convolution will be $3 \times 4=12$ channels? Or those... |
H: Loss in multi-class classification
I have a multi-class classification task. One of the standard approach in choosing loss function is to use a CrossEntropyLoss. It is a good option when classes are standonlone and not similar to each other.
What if some classes are more similar?
For example, if I have 10 classes, ... |
H: Predict total responses to emails amongst multiple groups
I've got historical data about email characteristics (like time sent, length, topic etc.), and the respondents to these emails - I've got their IP, which is further linked to gender, domicile, employment status and so on.
The example of my datasets is shown ... |
H: sklearn models Parameter tuning GridSearchCV
Dataframe:
id review name label
1 it is a great product for turning lights on. Ashley 1
2 plays music and have a good sound. Alex 1
3 I love it, lots of fun. ... |
H: What is the difference between features in vgg
I read the architecture of the model but this is the first time I try to use it . The calculations of the features map will be different if I extract the features from the two last layers or from the last layer but does it will affect if I used it in another model.
AI:... |
H: improve LinearSVC
Dataframe:
id review name label
1 it is a great product for turning lights on. Ashley 1
2 plays music and have a good sound. Alex 1
3 I love it, lots of fun. Peter ... |
H: Creating and training a Multilayer perceptron model with few data
Are there any ways to create a deep multilayer perceptron model that is capable of making accurate regression predictions based on the training done using around 1000 unique data?
I'm currently working on a Kaggle challenge for predicting the amount ... |
H: Understanding Lagrangian equation for SVM
I was trying to understand Lagrangian from SVM section of Andrew Ng's Stanford CS229 course notes. On page 17 and 18, he says:
Given the problem
$$\begin{align}
min_w & \quad f(w) \\
s.t. & \quad h_i(w)=0, i=1,...,l
\end{align}$$, the Lagrangian can be given as fol... |
H: calibrated classifier ValueError: could not convert string to float
Dataframe:
id review name label
1 it is a great product for turning lights on. Ashley
2 plays music and have a good sound. Alex
3 I love it, ... |
H: I am attempting to implement k-folds cross validation in python3. What is the best way to implement this? Is it preferable to use Pandas or Numpy?
I am attempting to create a script to implement cross validation in data. However, the splits cannot randomly take any records, so the training and testing can be done o... |
H: Does BERT need supervised data only when fine-tuning?
I've read many articles and papers mentioning how unsupervised training is conducted while pre-training a BERT model. I would like to know if it is possible to fine-tune a BERT model in an unsupervised manner or does it always have to be supervised?
AI: The dist... |
H: ML : Found input variable with inconsistent numbers
I am trying an Retail ML project, but am stuck on the Error "Found input variables with inconsistent numbers of samples: [982644, 911]". I tired many thing & I know why this error occurs, but I can't figure out a solution for it. Can anybody please help me. I've b... |
H: Answering the question of "WHY" using AI?
We have seen lots of natural occurrences that are happening in the whole world. Since we have great progress in technology and in particular AI, How can I employ ML to answer the question of WHY. In a sense that, without interpreting the result by human, Can machine interpr... |
H: Trained model performs worse on the whole dataset
I used pytorch as the training framework and the official pytorch imagenet example to train the image classification model with my custom dataset.
My custom dataset has 2 different label (good and bad), and over 1 million images.
I splitted the dataset into a traini... |
H: Where do Q vectors come from in Attention-based Sequence-to-Sequence Transformers?
I'm taking a course on Attention-based NLP but I'm not understanding the calculation and application of Attention, based on the use of Q, K, and V vectors. My understanding is that the K and V vectors are derived from the encoder in... |
H: Understanding SVM's Lagrangian dual optimization problem
I was going through SVM section of Stanford CS229 course notes by Andrew Ng. On page 18 and 19, he explains Lagrangian and its dual:
He first defines the generalized primal optimization problem:
$$ \begin{align}
\color{red}{ \min_w } & \quad \color{red}{f(w)... |
H: Assess the goodness of a ML generative model (text)
Take a RNN network fed with Shakespeare and generating Shakespeare-like text.
Once a model seems mathematically fine, as can be assessed by observing its loss and accuracy over training epochs, how can one assess and refine the goodness of the result ?
Only human ... |
H: Difference between ReLU, ELU and Leaky ReLU. Their pros and cons majorly
I am unable to understand when to use ReLU, ELU and Leaky ReLU.
How do they compare to other activation functions(like the sigmoid and the tanh) and their pros and cons.
AI: Look at this ML glossary:
ELU
ELU is very similiar to RELU except ... |
H: scikit-learn OneHot returns tuples and not a vectors
First I do a label encoding to all the columns that are strings so they will be numeric.
After that, I take just the columns with the labels, convert them to np array, reshape, and convert them to one-hot encoding.
The "y" is of size 900 (of floats), and in the r... |
H: Data extraction using crawlers
I have a rather simple data scraping task, but my knowledge of web scraping is limited. I have a excel file containing the names of 500 cities in a column, and I'd like to find their distance from a fixed city, say Montreal. I have found this website which gives the desired distance (... |
H: What does "regularization" actually refer to?
I am familiar with regularization, where we add a penalty in our cost function to force the model to behave a certain way. But is this a definition of regularization?
Typically we regularize to get a "simpler" model in some sense. But we could easily create a penalty fu... |
H: How are scores calculated for each class of binary classification
The formula for Precision is TP / TP + FP, but how to apply it individually for each class of a binary classification problem,
For example here the precision, recall and f1 scores are calculated for class 0 and class 1 individually, I am not able to... |
H: How does Gradient Descent work?
I know the calculus and the famous hill and valley analogy (so to say) of gradient descent. However, I find the update rule of the weights and biases quite terrible. Let's say we have a couple of parameters, one weight 'w' and one bias 'b'. Using SGD, we can update both w and b after... |
H: Keras: Custom output layer for multiple multi-class classifications
Hello, I’m quite new to machine learning and I want to build my first custom layer in Keras, using Python. I want to use a dataset of 103 dimensions to do classification task. The last fully connected layer of the model has 103 neurons (represente... |
H: How to choose embedding size for tensorflow recommender system
I am going to build a recommender system using TensorFlow recommender and the two-tower-model. I have wondered, how to choose the size of the embedding dimension. Are there any papers on this for large scale recommender systems? For the example, Google ... |
H: Confusion matrix terminology
I am working on machine learning with a supervised problem with 2 classes: NO and YES, and I need some precision about confusion matrix. I read 2 differents terminologies, some writes matrix confusion as:
$$
\begin{pmatrix}
& &\text{Positive Prediction} &\text{Negative Prediction}\\
... |
H: Machine learning accuracy for not a class-imbalanced problem
I would like know if the accuracy has an impact on not class-imbalanced dataset ? I know that accuracy is sensitive to class-imbalance and also always good to be able to appreciate precision and recall values.
Is it also the case to not class-imbalanced d... |
H: Is standardization/normalization a good way of reducing the impact of outliers when I'm training a machine learning model?
Recently, I have read some papers in which the authors state that they have performed standardization/normalization of the variables for reducing the impact of outliers in the machine learning ... |
H: Difference in result in every run of Neural network?
I have written a simple neural network (MLP Regressor), to fit simple data frame columns. To have an optimum architecture, I also defined it as a function to see whether it is converging to a pattern. But every time that I run the model, it gives me a different r... |
H: Where can I find study materials?
Can anyone recommend me some material (books, blogs, youtube channels, ...) to study statistics, Machine Learning and in general Data Science topics?
Thanks
AI: Deep Learning Specialization on Coursera: You can follow the lectures for free or apply for a scholarship if you can't af... |
H: Explanation of Karpathy tweet about common mistakes. #5: "you didn't use bias=False for your Linear/Conv2d layer when using BatchNorm"
I recently found this twitter thread from Andrej Karpathy. In it he states a few common mistakes during the development of a neural network.
you didn't try to overfit a single bat... |
H: Is there any difference between classifying images by their type and by the objects they represent?
Let us suppose that I would like to train a machine learning model for classifying images according to their types (for example, photographs and drawings).
The techniques that I can use for this would be different fr... |
H: Software/Library Suggestion: Is there a usable open-source sequence tagger around?
(Not sure if this is the right community for the question - please do downvote if stats. or whatever else is more appropriate...)
I'm looking for a suggestion for either a command-line tool or library (preferably Python or Ruby, but ... |
H: What package, software or particular tool produced this bar plot?
Would anyone be able to identify the package or tool used to created this particular bar plot? It has a distinctive font.
Source (with paywall): https://towardsdatascience.com/stopping-covid-19-with-misleading-graphs-6812a61a57c9
AI: This seems to b... |
H: What tool can I use for produced this type of lines in a multiple line graph?
I was viewing a video about the declination in fertility rates when I saw a good line chart. This is a multiple graphs line and each line have different form this can be useful for readers don't get confused comparing the lines because th... |
H: Determining if a dataset is balanced
I'm learning about training sets and I have been provided with a set of labelled customer data that segments customers into one of two classes: A or B. The dataset also contains gender, age and profession attributes for each customer. The distribution of classes in the dataset i... |
H: Understanding deconvolutional network loss function
In the paper (1), there is a description of a deconvolutional network.
The loss function (with only one layer) compares the colour channels of the orignal image with the colour channels of the generated image. To increase the sparsity of the feature maps there is ... |
H: Removing the outliers improved my models, is what I did good or bad?
I used cross validation on my data (11000 rows) with maximum salary of 10000 and after some cleaning I got to rmse=70. Then I tried to remove the outliers 10 times just to try things now I have 9000 rows with maximum salary of 260, I got rmse=23. ... |
H: Steps of multiclass classification problem
So this question is more theoretical, than a practical one. I got a dataframe with 4 classes of cars' body types (e.g. sedan, hatchback, etc.) and different characteristics (doors, seats, maximum speed, etc.). The goal is to build a model, which predicts class by means of ... |
H: Does gradient descent always find global minimum for specific regression type?
From my understanding, linear regression is used for predicting an output based on an input using a linear equation that is optimally fitted to some input data. We choose the best fitted linear equation for some input data using a loss f... |
H: Normalization factor in logistic regression cross entropy
Given that probability of a matrix of features $X$ along with weights $w$ is computed:
def probability(X, w):
z = np.dot(X,w)
a = 1./(1+np.exp(-z))
return np.array(a)
def loss(X, y, w):
normalization_fator = X.shape[0] #store loss values
... |
H: CRFSuite/Wapiti: How to create intermediary data for running a training?
After having asked for and been suggested two pieces of software last week (for training a model to categorize chunks of a string) I'm now struggling to make use of either one of them.
It seems that in machine learning (or at least, with CRF?)... |
H: Cleaning rows of special characters and creating dataframe columns
Below is my Dataframe format consisting of 2 columns (one is index and other is the data to be cleaned)
0 ans({'A,B,C,Bad_QoS,Sort'})
1 ans({'A,B,D,QoS_Miss1,Sort'})
I want to remove special characters
create a data frame for all comma separat... |
H: Why deep learning models still use RELU instead of SELU, as their activation function?
I am a trying to understand the SELU activation function and I was wondering why deep learning practitioners keep using RELU, with all its issues, instead of SELU, which enables a neural network to converge faster and internally ... |
H: Does One-Hot encoding increase the dimensionality and sparsity of dataset?
There are two ways to convert object datatype into numeric datatype, first is One-Hot encoding and second is simply map the numerical tags to different values.
For example for column Age containing three distinct values 'child', 'adult' and ... |
H: Comparing accuracies of Grid Search CV & Randomized Search CV with K-Fold Cross Validation?
Are Grid Search CV & Randomized Search CV always/necessarily supposed to give more accurate results after hyperparameter tuning as compared to K-Fold Cross Validation?
AI: From your comment above, " though Grid & Radom Searc... |
H: Tune learning rate while tuning other HP
When doing hyperparameters optimisation, like a Random Search, should you add a search space for the learning rate ?
My intuition is that some HP might work better with a certain LR, and be sub-optimal with a lower LR. But if I add LR to the search space, I fear that the ran... |
H: problem with using f1 score with a multi class and imbalanced dataset - (lstm , keras)
I'm trying to use f1 score because my dataset is imbalanced. I already tried this code but the problem is that val_f1_score is always equal to 1. I don't know if I did it correctly or not. my X_train data has a shape of (50000,30... |
H: Multiple models have extreme differences during evaluation
My dataset has about 100k entries, 6 features, and the label is simple binary classification (about 65% zeros, 35% ones).
When I train my dataset on different models: random forest, decision tree, extra trees, k-nearest neighbors, logistic regression, sgd, ... |
H: Robustness vs Generalization
I don't quite understand the difference between robustness and generalisability in relation to image processing (CNN). If my model generalises well, it is also robust to changes in the image material. Unfortunately, I haven't found any concrete definitions or other materials that descri... |
H: when I only give command 'fit', my class does 'transform' too
I have created 2 classes, first of which is:
away_defencePressure_idx = 15
class IterImputer(TransformerMixin):
def __init__(self):
self.imputer = IterativeImputer(max_iter=10)
def fit(self, X, y=None):
self.imputer.fit(... |
H: Number of parameters in CNN
I'm trying to understand the convolutional neural network and especially its parameters. I found several formulas on the internet, but I cannot understand them. For example:
((filter_size*filter_size)*stride+1)*filters)
What is the number of filters here? Does it mean, that we train dif... |
H: How to improve the result of f1 on imbalanced dataset
I have a dataset in which these are the distribution of the data:
Neutral. 15000
Negative 3000
positive 2000
And I am mostly interested to improve the performance on the negative category. I would say neutral and positive are not important for me. And I am u... |
H: Why scikit-learn's sequential feature selection requires how much features to be selected beforehand?
From the version 0.24, the scikit-learn has new method 'SequentialFeatureSelector', which adds (forward selection) or removes (backward selection) features to form a feature subset in a greedy fashion. It lets us ... |
H: Correct approach to scale (min-max scaler) both input and output signal data for unsupervised learning?
I am working on a denoising autoencoder problem with noisy and clean signals. Before I pass the signals to my model I want to apply min-max normalization and am unsure of the correct way to apply this.
The model ... |
H: Google's Bayesian Structural Time-Series
I am attempting to get my head around Google's Causal Impact paper, which isn't completely clear to me.
In the methodology part of the paper, the authors say: "The framework of our model allows us to choose from among a large set of potential controls by placing a spike-and-... |
H: Improving text classification & labeling in imbalanced dataset
I am trying to classify text titles (NLP) in categories. Let us say I have 6K titles that should fall into four categories.
My questions:
I do not understand why in some ML techniques categories are converted into numerical values "Transforming the pre... |
H: Meaning of NER Training values using Spacy
I am trying to train custom entities using Spacy. During the training process I am getting number of values of LOSS, score etc. What is the meaning of these values
============================= Training pipeline =============================
ℹ Pipeline: ['tok2vec', 'ner']
... |
H: Best platform to work with when having millions of rows in dataframe
I have table with around 20 features and millions of observations (rows).
I need to create model base on this table, however, as it is huge, training models like random forest or XGB takes forever. I'm working mainly with scikit-learn and the XGBo... |
H: Understanding Sklearns learning_curve
I have been using sklearns learning_curve , and there are a few questions I have that are not answered by the documentation(see also here and here), as well as questions that are raised by the function about sklearn more generally
Here are some learning curves from my models of... |
H: Creating a DataFrame in Pandas from a numpy array and a list
labels is
array([3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
3, 0, 2, 2, 2, 2, 2... |
H: What is the difference between batch_encode_plus() and encode_plus()
I am doing a project using T5 Transformer. I have read documentations related to T5 Transformer model. While using T5Tokenizer I am kind of confused with tokenizing my sentences.
Can someone please help me understand the difference between batch_e... |
H: difference between novelty, concept drift and anomaly
Concept drift is when the relation between the input
data and the target variable changes over time. like changes in the conditional distribution.
is novelty an outlier? what should I think of?
what is the difference between concept drift and novelty and anomaly... |
H: Keras ImageDataGenerator unable to find images
I'm trying to add image data to a Kaggle notebook so I can run a convolutional neural network but I'm having trouble doing this via ImageDataGenerator. This is the link to my Kaggle notebook
These are my imports:
import numpy as np # linear algebra#
import pandas as p... |
H: Churn prediction model doesn't predict good on real data
I am working currently on churn prediction problem.
As an input I use data from date warehouse for a period 082016 - 032021(one row per month for each customer).
Based on this data I have created a time window of 18 months, where I track customer behaviour(fe... |
H: How to write a reward function that optimizes for profit and revenue?
So I want to write a reward function for a reinforcement learning model which picks products to display to a customer. Each product has a profit margin %.
Higher price products will have a higher profit margin but lower probability of being purch... |
H: log(odds) to p formulation
$$Log(Odds) = log({p \over (1-p)}) $$
$${p \over (1-p)} = e^{b+b_1x_1+....}$$
I understand up to here, however how does this:
$$p = (1-p) e^{b+b_1x_1+...}$$
become:
$$ p = {1 \over {1+e^{-(b+b_1x_1+...)}}}$$
Can someone explain last two steps?
AI: We have, $p = (1 - p)e^{b + b_1x_1 + \ldo... |
H: Interpreting evaluation metrics with threshold/cutoff
I was doing churn prediction for a company. I've got the following results by applying 3 classifier.
Model
Accuracy
AUC
Logistic Regression
0.671
0.736
Decision Tree (pruned)
0.681
0.665
Decision Tree unpruned
0.623
0.627
Now, I want to know two ... |
H: How do I minimizie cost for EV charging?
I want to find a charging schedule that minimize cost of charging an EV.
The main objective is to have a fully charged car for the next morning, but the sub objective is to minimize cost based these two things combined:
Charge when electricity is cheapest - I know the hourl... |
H: Is it necessary to use stratified sampling if I am using SMOTE already?
I have already applied SMOTE to my imbalanced dataset with more than 300K observations. Does it still make sense to use stratified K-fold cross validation rather than simply ordinary K-fold cross validation (seems unlikely each of the K-fold tr... |
H: What does "S" in Shannon's entropy stands for?
I see many machine learning texts using the following notation to represent Shannon's entropy in classification/supervised learning contexts:
$$
H(S) = \sum_{i \in Y}p_i \log(p_i)
$$
Where $p_i$ is the probability of a given point being of class $i$. I just do not unde... |
H: why is the BERT NSP task useful for sentence classification tasks?
BERT pre-trains the special [CLS] token on the NSP task - for every pair A-B predicting whether sentence B follows sentence A in the corpus or not.
When fine-tuning BERT for sentence classification (e.g. spam or not), it is recommended to use a dege... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.