## Screening (multi)collinearity in a regression model

The kappa() function can be of assistance. ...READ MORE

## Which polynomial regression degree is significant ? depends of number of points or other parameters?

You're more likely to overfit the results ...READ MORE

## What is the difference between a Confusion Matrix and Contingency Table?

Confusion Matrix is a classification matrix used ...READ MORE

## How to perform regression algorithm on a textual data(IMDB reviews)?

You can use either word2vec or tf-idf ...READ MORE

## probability of getting three of a kind by drawing 5 cards

from collections package import counter to count ...READ MORE

## How to get early stopping for lasso regression

I believe you're referring to regularization. In ...READ MORE

## How do I create a linear regression model in Weka without training?

Weka is a classification algorithm. This is ...READ MORE

## Competitive Programming Algorithm Sock Drawing Probability Question

Another way to look at the problem ...READ MORE

## Naive Bayes classifier bases decision only on a-priori probabilities

You seem to have trained the model ...READ MORE

## How does software that calculates winning probability of a Texas Hold'em or Omaha hand against 8 random opponent hands work?

The projected win rate, as you noted, ...READ MORE

## Probability: the one true fish

What you're looking for is P(A|B), which ...READ MORE

## Linear Discriminant Analysis vs Naive Bayes

There are no standards fixed as to ...READ MORE

## Formula to calculate chance (probability) of a dice side based on its value

If I understand you correctly, you're looking ...READ MORE

## Logistic regression coefficient meaning

What did the intercept teach you? It's ...READ MORE

## How to calculate ctc probability for given input and expected output?

The loss for a batch is defined ...READ MORE

## sklearn MLPClassifier - zero hidden layers (i.e. logistic regression)

You could try something like this. my_nn = ...READ MORE

## Bad logistic regression in trivial example [scikit-learn]

This is due to the process of ...READ MORE

## How does Label Encoder assigns the same number?

I am creating a dummy data set ...READ MORE

## DBSCAN algorithm and clustering algorithm for data mining

You can use any distance function with ...READ MORE

## Probability that a formula fails in IEEE 754

It is feasible to evaluate these things ...READ MORE

## What's the difference between regression testing and mutation testing?

Regression testing is a test suite that ...READ MORE

## Why is random_state required for ridge & lasso regression classifiers?

This is because the regression coefficients of ...READ MORE

## Getting one word as caption with zero probability using pretrained checkpoints for image captioning-im2txt

captiongenerator.py is a Python script that generates ...READ MORE

## Is predicting number of sales a Regression or Classification problem?

The output will be discrete but the ...READ MORE

## Why there is the need of using regularization in machine learning problems?

In Machine Learning we often divide the dataset ...READ MORE

## Classification vs Regression?

You are correct: categorization applies a label ...READ MORE

## Difference between Regression and classification in Machine Learning?

The goal of regression is to forecast ...READ MORE

## Empirical probability in R with x1+x2>2*x3

It's easy to duplicate random draws with ...READ MORE

## How to export regression equations for grouped data?

First, you'll need a linear model with ...READ MORE

## Is batch normalization useful for small networks?

Batch normalization is a technique that is ...READ MORE

## difference between a cost function and the gradient descent equation in logistic regression?

Cost function is a way to evaluate ...READ MORE

## Choose specific number with probability

Examine the sample function. set.seed(1) sample(c(0,1), size=12, replace=TRUE, prob=c(0.2,0.8)) 1 ...READ MORE

## Leela Chess Zero: how large is the probability vector in the output layer?

The next move's probability vector (called the ...READ MORE

## How to resolve heteroscedasticity in Multiple Linear Regression in R?

Try to use a different form of ...READ MORE

## feature selection for regression vs classification

There are various feature selection processes used ...READ MORE

## What does regression test mean?

Regression testing is used to ensure that ...READ MORE

## Can we use Normal Equation for Logistic Regression ?

Well not likely,  only one discriminative method ...READ MORE

## What does dimensionality reduction mean?

Dimensionality reduction is used in Machine Learning ...READ MORE

## Difference between classification and regression, with SVMs

What is the exact difference between a ...READ MORE

## Training and testing data in machine learning

Unsupervised learning is used with the K-means ...READ MORE

## What is the difference between supervised learning and unsupervised learning?

Supervised and unsupervised learning are two types ...READ MORE

## Alternatives to linear regression for dataset with many points with small value and some extreme values

The above situation is the case where ...READ MORE