Box and Whisker Plots of Classification Accuracy vs Repeats for k-Fold Cross-Validation

Repeated k-Fold Cross-Validation for Model Evaluation in Python

The k-fold cross-validation procedure is a standard method for estimating the performance of a machine learning algorithm or configuration on a dataset. A single run of the k-fold cross-validation procedure may result in a noisy estimate of model performance. Different splits of the data may result in very different results. Repeated k-fold cross-validation provides a […]

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Histogram of Each Variable in the Diabetes Classification Dataset

How to Selectively Scale Numerical Input Variables for Machine Learning

Many machine learning models perform better when input variables are carefully transformed or scaled prior to modeling. It is convenient, and therefore common, to apply the same data transforms, such as standardization and normalization, equally to all input variables. This can achieve good results on many problems. Nevertheless, better results may be achieved by carefully […]

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