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H: Flattening output before calculating metrics
I use scikit-learn to calculate precision, recall and f1 scores which only accept 1D arrays, but my model's outputs are 2D (binary segmentation maps). My question is, is it ok to simply flatten the outputs, or is there some other function I should use to calculate the me... |
H: How to disable GPU with TensorFlow?
Using tensorflow-gpu 2.0.0rc0. I want to choose whether it uses the GPU or the CPU.
AI: I've seen some suggestions elsewhere, but they are old and do not apply very well to newer TF versions. What worked for me was this:
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
When t... |
H: Decision Tree split error
During the split function of the decision tree, I am getting an assertion error stating:
Error > Assert: type(C) == dict
I couldn't find any errors in the code up until now. Could you please correct it if there is any problem with it?
My code:
def split(X,Y,i):
def __find_best_split(... |
H: Hinge loss question
Hinge loss is usually defined as
$$L(y,\hat{y}) = max(0,1-y\hat{y}) $$
What I don't understand is why are we comparing zero with $1-y\hat{y}$ instead of some other constant. Why not make it $2-y\hat{y}$, or $\sqrt2-y\hat{y}$ or just take $y\hat{y}$, to check if the observation would be on the r... |
H: Delete/Drop only the rows which has all values as NaN in pandas
I have a Dataframe, i need to drop the rows which has all the values as NaN.
ID Age Gender
601 21 M
501 NaN F
NaN NaN NaN
The resulting data frame should look like.
Id Age Gender
601 21 M
501 NaN ... |
H: Identifying if the sentence if it comprise information about education
Given a sentence I am trying to classify if the sentence contain information about education. For example:
sentence1 = "Require minimum four years of professional degree."
sentence2 = "no degree required for this job."
For identifying as a fir... |
H: Understanding the "Wide" part of Google's wide and deep
Google's wide and deep recommender model sounds really cool, but I'm struggling to believe I'm grasping the wide section right so wanted to check my understanding.
Their paper says the following:
The wide component consists
of the cross-product transform... |
H: Why the Logistic regression model trained with tensorflow performed so poor
I trained a logistic regression model with tensorflow but the accuracy of the model was so poor (accuracy = 0.68). The model was trained using simulated dataset and the result should be very good. is there something wrong with the code ?
#... |
H: sklearn.accuracy_score(y_test, y_predict) vs np.mean(y_predict == y_test)
What is the difference between these two methods for finding model accuracy?
I have used both methods in python3 and i normally get identical results. However in few cases i get completely different results, so I am trying to figure out the p... |
H: Binary classfication vs One-class classification
Why do we need samples of both classes for the training of binary classification algorithms, if one-class algorithms can do the job with only samples from one class?
I know that one-class algorithms (like one-class svm) were proposed with the absence of negative data... |
H: CNNs: understanding feature visualization Channel Objectives (SOLVED)
I'm trying to follow a paper on deep NN feature visualization using beautiful examples from the GoogLeNet/Inception CNN. see: https://distill.pub/2017/feature-visualization/
The authors use backpropagation to optimize an input image to maximizes ... |
H: Accuracy noise patterns during model training
I'm training a logistic regression model on a small dataset. I have about 1300 samples that I split into a training and a testing set (70% and 30% respectively).
The training seems ok, however when I plot the accuracy of my model w.r.t. the epoch, some repeating noisy p... |
H: how to create multiple plot from a panda Dataframe
I want to plot multiple plots.
The data is stored in a pandas dataframe and each row should be a seperate plot.
Each row has an ID (ZRD_ID) which doenst matter and a date (TAG) and 24 values to be plotted.
import pandas as pd
import numpy as np
df = pd.read_csv('.... |
H: Why does accuracy remain the same
I'm new to machine learning and I try to create a simple model myself. The idea is to train a model that predicts if a value is more or less than some threshold.
I generate some random values before and after threshold and create the model
import os
import random
import numpy as ... |
H: Multi-Output Regression with neural network in Keras
I have got an .xlsx Excel file with an input an 2 output columns. And there are some coordinates and outputs in that file such as:
x= 10 y1=15 y2=20
x= 20 y1=14 y2=22 ...
I am trying to do that regression using tensorflow. But somehow i can't manage to do it. I a... |
H: Python Pandas agregation
I have a data set recording daily values of several metrics say R1, R2, for example:
Date Metric cur_val Mgmt_Lmt
1/1/2019 R1 38.94927536 100
1/2/2019 R1 38.83188406 100
1/3/2019 R1 38.71449275 100
1/4/2019 R1 38.59710145 100
1/5/2019 R1 38.47971014 100
1/6/2019 ... |
H: Finding correlation between MNIST digits
What way would be correct to calculate the correlation between say digit '1' and digit '7' images from MNIST? Taking average values of all digit '1' pixels and digit '7' pixels to compute correlation between those would be a correct?
AI: You can’t. Correlation is a measure o... |
H: Keras ANN Trained Model's Accuracy change on prediction
I have trained an ANN Binary classifier using Keras. It gives 90% accuracy.
After testing when I predict same data again but pass only one class then accuracy decreases to 40%.
I have figured out that if I pass mixed classes while predicting then it will giv... |
H: Fine-tuning a Pre-trained model (Resnet50) do I need to validate it or just train it?
When fine-tuning a Resnet50 model should I do the standard train validation split and train like any normal CNN or should I just do the training and not the validation if I am going to use this model as a base model in another mor... |
H: Data Reshaping for CNN using Keras
I'm a beginner in Keras. I've loaded MNIST dataset in Keras and checked it's dimension.
The code is
from keras.datasets import mnist
# load data into train and test sets
(X_train, y_train), (X_test, y_test) = mnist.load_data()
print(X_train.shape)
print(y_train.shape)
print(X_te... |
H: how to pass parameters over sklearn pipeline's stages?
I'm working on a deep neural model for text classification using Keras. To fine tune some hyperparameters i'm using Keras Wrappers for the Scikit-Learn API.
So I builded a Sklearn Pipeline for that:
def create_model(optimizer="adam", nbr_features=100):
mode... |
H: why multiplication (squares) doesn't work for neural networks?
Below code creates the sum of 2 random numbers and then we train for 1000 examples and then we are able to predict which works fine.
Consider the below code for creating random data :
def random_sum_pairs(n_examples, n_numbers, largest):
X, y = list... |
H: What I'm doing wrong with my CNN Keras?
In my project I have 700 images for each class (pdr and nonPdr) totalizing 1400 images. To validation I've put 28 samples.
The problem is that my validation loss and accuracy is unstable. This is my code:
def ReadImages(Path):
LabelList = list()
ImageCV = list()
c... |
H: Understanding python XGBoost model dump output of a very simple tree
I am trying to understand the model dump output from XGBoost. I would like to step through and see exactly how the model arrived at it's prediction. To simplify I trained a model with 1 tree and 1 max depth, and as expected all records get one of ... |
H: Improving classifcation when some are less represented?
I have a multi-class classification problem. It performs quite well but on the least represented classes it doesn't. Indeed, here is the distribution :
And here are the classification results (I took the numbers off the labels):
.
Therefore how to improve cla... |
H: How to install boruta in conda?
I want to install boruta in my anaconda environment, but if I execute
conda install boruta
It displays:
PackagesNotFoundError: The following packages are not available from current channels:
- boruta
Current channels:
- https://repo.anaconda.com/pkgs/main/linux-64
- https:/... |
H: Infer family type, size from reviews
I have a bunch of reviews:
User_id, review
1, "We (a family of 4 adults) chose this and view and loved this place"
1, "My husband and I, with our 2 teen sons, visit this restaurant at least once..."
2,"My partner and I booked table for a short holiday, their wine menu was awesom... |
H: SVM hyperplane margin
so that $H_0$ is equidistant from $H_1$ and $H_2$.
However, here the variable $\delta$ is not necessary. So we can set $\delta=1$ to simplify the problem.
$$w\cdot x+b=1 $$
and
$$w\cdot x+b=−1$$
Why is this assumption is taken? If it is taken, we can get the distance between two planes as $2... |
H: NMT, What if we do not pass input for decoder?
For transformer-based neural machine translation (NMT), take English-Chinese for example, we pass English for encoder and use decoder input(Chinese) attend to encoder output, then final output.
What if we do not pass input for decoder and consider it as a 'memory' mode... |
H: Counting the transition in a dataframe overtime
I am stuck at a problem and am thinking how to come out of it. I want to write a code in python with dataframe as below:
data = {'Id':['a', 'a', 'b', 'b', 'c', 'c'],
'value':['Active', 'Notactive', 'Active', 'Superactive', 'Notactive', 'Superactive'],
... |
H: Policy gradient vs cost function
I was working with continuous system RL and obviously stumbled across this Policy Gradient.
I want to know is this something like cost function for RL? It kinda gives that impression considering we are finding out how efficient the system is as a whole (weighted sum of rewards mult... |
H: Pyspark Matrix Transformation
Let's assume I have the following dataframe in PySpark:
Customer | product | rating
customer1 | product1 | 0.2343
customer1 | product2 | 0.4440
customer2 | product3 | 0.3123
customer3 | product1 | 0.7430
There can be several customer product combinations but... |
H: Difference of sklearns accuracy_score() to the commonly accepted Accuracy metric
I am trying to evaluate the accuracy of a multiclass classification setting and I'm wondering why the sklearn implementation of the accuracy score deviates from the commenly agreed on accuracy score: $\frac{TP+TN}{TP+TN+FP+FN}$
For skl... |
H: How does the given data gets plotted on a graph
I come from a programming background and learning the math behind the data science and algorithms now.
I would like to understand the logic behind how a data gets plotted in a graph when using Logistic regression.
Lets consider a Testing data like this,
ID Age Grade... |
H: What technique to use in order to identify what position an audio sample is at in a longer audio sample?
I am interested in what techniques and algorithms could be used in order to tackle the following problem:
I have a database of audio samples, specifically live performances of various songs. I have about a dozen... |
H: True positives and true negatives, F1 score: multi class classification
I have 4 classes for an application of classification of animal kingdom: 1 --> invertibrates; 2 --> vertibrates; 3--> mammal; 4 ---> ambhibian. Given a mixture of images the objective is to identify mammals correctly. In the confusion matrix fo... |
H: The effect of imbalanced distribution of data
I read on Google's ML website if I have classification dataset with a ratio of 90% for one classification and 10% of the data for another classification.
In that case, should I use the exact same percentage of data for each classification?
i.e. deleting around 80% of th... |
H: Feature selection is not that useful?
I've been doing a few DataScience competitions now, and i'm noticing something quite odd and frustrating to me. Why is it frustrating? Because , in theory, when you read about datascience it's all about features, and the careful selection, extraction and engineering of those to... |
H: Is it possible to create a rule-based algorithm to compute the relevance score of question-answer pair?
In information retrieval or question answering system, we use TD-IDF or BM25 to compute the similarity score of question-question pair as the baseline or coarse ranking for deep learning.
In community question an... |
H: How to get Keras accuracy for each step in an epoch like in Tensorflow?
Like in tensorflow I get accuracy for each step -
Step 1, Minibatch Loss= 68458.3359, Training Accuracy= 0.800
Step 10, Minibatch Loss= 451470.3125, Training Accuracy= 0.200
Step 20, Minibatch Loss= 582661.1875, Training Accuracy= 0.200
Step 3... |
H: (Python Basic) more elegant way of creating a dictionary
Is there a more elegant way to write a code like this?
my_dic = {
'Model':['Apple', 'Banana', 'Pineapple', 'Melon', 'Orange', 'Grape'],
'AAA':[
method1(y, y_Apple),
method1(y, y_Banana),
method1(y, y_Pineapple),
met... |
H: What do you call a feature that always has the same value?
Is there a standard term for a feature that always has the same value, i.e. that can be discarded without loss of information?
For example I am trying to classify cats vs dogs, and every example in my training set has has_two_eyes=true.
I am thinking someth... |
H: Validation Curve Interpretations for Decision Tree
I'm working on a machine learning class, and we're using supervised learning right now, starting with decision trees. I'm using the UCI Credit Card dataset (whether or not certain people will default in their payments due to past history).
Using a decision tree cla... |
H: Transform test data when using a persistent model
I'm quite new to data science and only slowly following the necessary steps to get valid results using scikit-learn. As far as I understand you fit and transform the training data and only transform the test data (using the parameters retrieved by the earlier fittin... |
H: (Feature Selection) different results from L2-based and Tree-based
I am doing feature selection using Sklearn:
Tree-based feature selection : RandomForestClassifier.feature_importances_
L2-based feature selection: LogisticRegression.coef_
Target variable is binary classes. The training set is standardized.
How sh... |
H: Checking if ML model is possible
How can I check if a machine learning model is feasible on a given dataset? What techniques like EDA, correlation etc. can be used to judge if a model is possible i.e. data and predictor variables will give reasonably accurate forecasts or in other words there is good enough signal ... |
H: Using a trained Model from Pickle
I trained and saved a model that should predict a sons hight based on his fathers height.
I then saved the model to Pickle.
I can now load the model and want to use it but unfortunately a second variable is demanded from me (besides the height of the father) I think I did something... |
H: How to save/load a Model (Pickle) with a specific path/directory
I seems like a very basic think but I couldnt find an answer to it.
I want to save my model to a specific directory using pickle.
The two algorithms below work fine for saving it in the same directory as the code itself but I want to save all my model... |
H: How to validate a clustering model without a ground truth?
Im dealing with a dataset (text messages about source code comments) that are not labeled. I don't have a assumption about the implicits classes in this dataset. I want to discovery (by clustering) the common hidden patterns shared by the groups of messages... |
H: shapes (127,1) and (13,) not aligned: 1 (dim 1) != 13 (dim 0)
i am try to find score of linear regression
it gives me this type error my code is below
from sklearn import datasets
bostan=datasets.load_boston()
x=bostan.data
y=bostan.target
from sklearn import preprocessing
x_scale=preprocessing.scale(x)
yfrom ... |
H: Meaningful and Non-Meaningful Data?
I can understand what meaningful data is like its important information that can be used to evaluate something but I don't get what non-meaningful data is? Is it less important data?
AI: "meaningful" is a vague word anyway, but yes you got the idea: in the context of a particular... |
H: Classification vs Regression Model what should I choose?
I am working on a problem like 'customers next month revenue prediction'. Here revenue will be the target variable. Again we actually segment the customers based on there revenue(like if they give less than 200 they will be in category 'A' else 'B'). I have t... |
H: Best way to visualize huge amount of data
I have a data set of around 3M row. I has only 2 category (category- 2:1 ratio). Now i want to visualize(scatter plot) it's distribution to understand can the data linearly separable or not(In order to choose model type).I already try this and the plot is not understandable... |
H: Confusion for considering accuracy or standard deviation in selecting the best parameters
I have a model with a various parameters to test.
The size of the dataset I have is not really large (~500 documents).
My issue is that when I test the parameters using 10 CV, some of them produce high accuracy value but the S... |
H: Why does the neural network keep giving out the same output for every input?
Made a neural network using TensorFlow's Keras that is supposed to match an IP to one of the 7 type of vulnerabilities and give out what type of vulnerability that IP has.
model = tf.keras.models.Sequential([
tf.keras.layers.Flatten(),
... |
H: Unsupervised Clustering for n-length word arrays
I have a series of arrays
[Apple,Banana,Cherry,Date]
[Apple,Fig,Grape]
[Banana,Cherry,Date,Elderberry]
[Fig,Grape]
and I would like to build some clusters that associate the arrays into groups based on overlap
Group1: Array1 and Array3 as they have 3 common words
Gr... |
H: Explanation behind the calculation of training loss in deep learning model
I am trying to model an image classification problem using convolution neural network. I came across a code on Github in which I am not able to understand the meaning of following line for loss calculation in the training loop.
I am omitting... |
H: How to Avoid rarely used discrete feature values in a dataset
On Google's ML crash course it states:
Good feature values should appear more than 5 or so times in a data
set. Doing so enables a model to learn how this feature value relates
to the label. That is, having many examples with the same discrete
val... |
H: Interpreting fraction of zero weights in TensorFlow
I am using the TensorFlow to do a simple linear classification using logistic regression. The graph included from the TensorBoard displays what they call the fraction of zero weights. How do I interpret this in terms of model evaluation? I am assuming this is goo... |
H: ValueError: Expected 2D array, got 1D array instead:
I was following this example online for simple text classification
And when I create the classifier object like this
from sklearn.datasets import fetch_20newsgroups
twenty_train = fetch_20newsgroups(subset='train', shuffle=True)
from sklearn.feature_extraction.t... |
H: XGBoost vs ARIMA for Time Series analysis
Doing time series analysis, I have doubts on choosing the right model. I want to predict the next 30 mins window, from the input dataset which contains the no. of error count for that particular 1 min interval.
Should I use XGBoost or ARIMA regressions?
Most of article or ... |
H: Machine learning method to predict event date
Let's say I have a big dataset consisting of variables including but not limited to the start/end date of loans, their notional amount, a loan prepayment indicator etc.
My goal is to create a model that will be trained on past data in order to predict the prepayment dat... |
H: How to find similar points to a positive set when you don't have any negative set?
The task I'm used to do is the following. A client comes to see me with a set of clients (called positive companies) and he wants me to find other similar prospects. Usually, he also gives me a set of negatives companies and I have a... |
H: what arguments should I pass to dbscan or optic in order to divide the data in a specific way
I have thousands of very similar datasets that needs to be divided in diagonal way to two groups.
for example:
and
I tried to play with the argument of dbscan and optic as epsilon and minPoints and even metric and none o... |
H: SMOTE vs SMOTE-NC for binary classifier with categorical and numeric data
I am using Xgboost for classification. My y is 0 or 1 (true or false). I have categorical and numeric features, so theoretically, I need to use SMOTE-NC instead of SMOTE. However, I get better results with SMOTE.
Could anyone explain why this... |
H: How to test hypothesis?
I have a table named app_satisfaction which has user_id, satisfaction, # of people they've invited.
I've grouped by satisfaction and found that on averge.
people in satisfaction ="BAD" group invted 2.25 people,
"GOOD" group invited 2.09 people, and
"EXECELLENT" group invited 1.89 people.
So ... |
H: how to use word embedding to do document classification etc?
I just start learning NLP technology, such as GPT, Bert, XLnet, word2vec, Glove etc. I try my best to read papers and check source code. But I still cannot understand very well.
When we use word2vec or Glove to transfer a word into a vector, it is like:
[... |
H: Analyzing Sentiments of Financial News related to a Company
I'm trying to build a model which gives me the sentiments of the Financial News related to a company and I want to predict the stock price accordingly. But the major problem that I'm facing is understanding the news for the counterpart.
Let's say I have a ... |
H: Predicted and true values distributions comparison
Is this alarming when a distribution of predicted values differs from a distribution of true values? I use xgbregressor and get the following plots
Usage of boxcox doesn't improve the case.
My data is spatial-temporal. I make a cash-flow forecasting for some city ... |
H: Multivariate Regression Error “AttributeError: 'numpy.ndarray' object has no attribute 'columns'”
I'm trying to run a multivariate linear regression but I'm getting an error when trying to get the coefficients of the regression model.
The error I'm getting is this: AttributeError: 'numpy.ndarray' object has no attr... |
H: Classifying Letters using CNN - Help
so some context, I'm trying to develop an OCR (for fun) and for that reason I decided to first find text within a page, parse it in to letters within the text and from there try and classify the letters that were extracted one by one.
For the classification I'm trying to build a... |
H: Forecasting time series outside the training/test set
I am trying to predict some time series based on precedent values using LSTM.
I have pretty good results when I compare the predicted time series with the test set (0,18% error)
I just miss how to forecast outside the interval of data ^^'
I have to admit that ... |
H: Classify if someone is home based on time
I have a dataset with locations and a timestamp of a subject. For each location and timestamp I determined by comparing the location to the home address if the subject was at home or not (0/1) and added this value to the dataset.
Now, I want to train a model to learn based ... |
H: What is the mean of inconsistent in machine learning and why 1NN is well known to be inconsistent
I really need help understanding the meaning of consistency in machine learning, why it's important, and why 1NN is considered to be inconsistent.
AI: Concistency of any algorithm in machine learning or statistics rat... |
H: Can a decision in a node of a decision tree be based on comparison between 2 columns of the dataset?
Assume the features in the dataframe are columns - A,B,C and my target is Y
Can my decision tree have a decision node which looks for say, if A>B then true else false?
AI: Yes, but not in any implementation that I a... |
H: How to deploy machine learning models as a chrome extension?
I have trained a stance detection model using SVMs. Wanted to know how can I deploy this as a chrome extensions. I do understand that the question is a bit broad but any links, suggestions etc. will be appreciated:)
AI: Since what you want to do is to app... |
H: Why don't we use space filling curves for high-dimensional nearest neighbor search?
Some space filling curves like the Hilbert Curve are able to map an n-dimensional space to a one dimensional line whilst preserving locality. Does that mean that we could map a dataset of high dimensional points to a line and expect... |
H: sklearn.metrics.average_precision_score getting different answers for same data but different formats
I was trying to learn how average precision (AP) is calculated and implemented in scikit-learn. I have read the documentation, but I don't think I fully understand it yet.
Consider the following two snippet:
import... |
H: Plotting Stacked Histogram for Time-series data
Given the dataset:
timestamp item itemcount
2019-03-18 07:40:08.759 A 10
2019-03-18 08:40:08.759 B 5
..................................................
2019-05-20 07:40:08.759 D 4
2019-05-21 07:... |
H: Publish without validation score?
My mentor wants me to write and submit an academic paper reporting a predictive model, but without any validation score.
Everything I have read in textbooks or the Internet says that this is wrong, but is there any case where only reporting a train score makes sense?
Background
The... |
H: Growth function of a 6-dimensional linear classifier
In our course, we are dealing with a d-dimensional classification problem
($\chi = \mathbb{R}^{d}$ as our input space, and $y = \{-1,+1\}$). Our hypothesis class $H$ consists of all hypotheses of the following form:
$h(x) = a\cdot \text{sign}(x_i - b)$, where $i ... |
H: Python : How to output graphs using lists method and how to change graph lines to "-" or "*"
Question
Please show me Python programming codes that shows graphs using the list method.
Moreover, I want to know how to change graph lines to "-" or "*".
Thank you for your answer in advance.
%matplotlib inline
import d... |
H: Minimum Possible Test MSE
I have a little confusion.
What follows is from Introduction to Statistical Learning (2013) by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani.
My understanding of what is going on is the following. The black curve is a function, let us say $y=f(x)$.
We have a random va... |
H: Neural Networks: Predicting probabilities of the possible values of y, instead of just predicting y
I have a true value y that I'd like to predict with a regression, but I'm interested in the probabilities that y will be different values. Y is theoretically continuous but in the dataset it is rounded to integers. L... |
H: Is it necessary to normalize data for XGBoost?
MinMaxScaler() in scikit-learn is used for data normalization (a.k.a feature scaling). Data normalization is not necessary for decision trees. Since XGBoost is based on decision trees, is it necessary to do data normalization using MinMaxScaler() for data to be fed to ... |
H: how to check all values in particular column has same data type or not?
I have column 'ABC' which has 5000 rows. Currently, dtype of column is object. Mostly it has string values but some values dtype is not string, I want to find all those rows and modify those rows. Column is as following:
1 abc
2 def
3 ghi
4 23
... |
H: Is it necessary to convert labels in string to integer for scikit_learn and xgboost?
I have a tabular data with labels that are in string. I will feed the data to decision trees in scikit_learn and XGBoost classifier.
Is it necessary to convert the labels in string to integers for these algorithms? Will the algorit... |
H: Multi-Output Regression with Keras
I am trying to do a multi-output regression using TensorFlow. I have got a dataset in Excel which includes a column of input points and 2 columns of output.
I converted all numbers to NumPy objects. And I am trying to do a basic regression but accuracy is always 1.0, I also want t... |
H: Training CNN for Regression
Background: I am using CNN to predict forces acting on a circular particle in a granular medium. Based on the magnitude of the forces, particle exhibits different patterns on its surface. The images are greyscaled 64-by-64 pixels. You can see different pictures with the magnitude of the ... |
H: Predict correct answer among ten answers for a given question
I have a case study to solve where I am given a dataset of questions and its answers, there are ten answers for a particular question.
It's a classification problem where correct answer is having class_label = 1 and all other nine answers having class_... |
H: Visualizing Variance / Standard Deviation for categories
Data Structure:
Method Category Variance for X
1 A 20
1 B 14
1 C 16
2 A 14
2 B 19
Where X was not used for classification, but is evaluation criteria. The o... |
H: Basic sympy problem in anaconda
I have enabled sympy on Anaconda to use it to solve basic linear equations, but whenever I try to type something up it gives me an error when defining the variables:
from sympy import *
x,y=symbols(’x,y’);
solution=solve((4*x-3*y-17,7*x+5*y-11),x,y);
P=(solution[x],solution[y]);
prin... |
H: How to find bias for perceptron algorithm?
My question is very basic. I am starting with ML and am working on the perceptron algorithm. I successfully computed the weights for this input data:
X = [[0.8, 0.1], [0.7, 0.2], [0.9, 0.3], [0.3, 0.8], [0.1, 0.7], [0.1, 0.9]]
Y = [-1, -1, -1, 1, 1, 1]
Output_weights = [-... |
H: If i no longer have access to feature in a data set should i retrain my model?
based on naive Bayes theorem if I no longer have access to the address book to tell whether the email author is known. Should I re-train the model, and if so, how?
AI: Naive Bayes, as far as I know, does not have any internal method of ... |
H: What is the meaning of the parameter "metrics" in the method model.compile in Keras?
I don't have very clear the meaning of the parameter metrics of the compile method of the class model in Keras:
model.compile(..., metrics = ['accuracy'], ...)
the documentation states:
List of metrics to be evaluated by the mode... |
H: Computing Jaccard Similarity between two documents
Data Mining:
Compute the Jaccard similarity of D1 and D2 on 2-shingles is. Sim(D1,D2) =
D1 = the quick brown fox jumps over the lazy dog
D2 = jeff typed the quick brown dog jumps over the lazy fox by mistake
Could you explain how to reach the conclusion, step-by-st... |
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So I have started my master thesis and I have been handed a time series dataset with 2000 rows and nearly 600 columns of data. I have dealt with time series before, but nowhere similar to this level of complexity. Many courses in time series only deals with univariate time series, ... |
H: How do you see the element of a csv table with many columns (>30) which the names of its columns is more than 10 character in pandas?
How do you see in pandas the element of a csv table with many columns (>25) which the names of its columns is more than 10 character?
I have 5000 rows and 32 columns and the label of... |
H: Predicting the speed of a car
I'm working on the commaai speedchallenge. The goal of the challenge is to predict the speed of a car based on a dashcam video. So far all the examples that I found (example 1, example 2) use some kind of method that takes in the information at frames $x_{t-h}, \ldots, x_{t-2}, x_{t-1}... |
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