ML Algorithms


Training and Testing In Machine Learning we create models to predict the outcome of certain events, to measure if the model is good enough, we can use a method called Train/Test. Train/Test is a method to measure the accuracy of your model. Bagging and Boosting Logistic Regression Naïve Bayes Random Forest Decision Tree K-Means Clustering Regularized Regression Models Linear Regression
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About the ML Algorithms category
ML Algorithms
0 134 September 10, 2021
What is k-fold cross-validation?
Training and Testing
0 18 November 8, 2022
How do you calculate the MSE in a linear regression model?
Linear Regression
0 24 November 8, 2022
How can you avoid overfitting your model?
Regularized Regression Models
0 15 November 8, 2022
What Is K-Means Clustering?
K-Means Clustering
0 43 October 4, 2022
Why isn't it recommended that you use Simple Linear Regression for Time Series data?
Linear Regression
2 538 May 5, 2019
Coefficients of Random Forest
Random Forest
2 2157 May 5, 2019
How to correct for heteroskedasticity in Linear Regression and coding help?
Linear Regression
2 906 May 4, 2019
Choosing an appropriate Train-Test Split Size
ML Algorithms
6 4144 April 23, 2019
Lasso Regression Vs Ridge Regression
Regularized Regression Models
9 670 April 17, 2019
Skewed Distributions
Regularized Regression Models
4 764 April 16, 2019
What does P-value signify about the statistical data?
ML Algorithms
4 666 April 15, 2019
R glmnet as.matrix() error message
Regularized Regression Models
2 6958 April 15, 2019
Overfitting using Random Forest
Random Forest
2 474 April 3, 2019
Step-wise regression using p values to drop variables with non-significant p values
Regularized Regression Models
4 630 April 3, 2019
KMeans Clustering Vs KNearest Neighbors
K-Means Clustering
4 436 March 18, 2019
Purity in Decision Trees: Gini Vs Entropy
Decision Tree
4 1001 March 1, 2019