I. Supervised Learning
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Hidden Markov Models Algorithms
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4) Cross-validation to reduce Overfitting
Cross-validation (CV) is part 4 of our article on how to reduce overfitting. Its one of the techniques used to test the effectiveness of a machine learning model, it is also a resampling procedure used to evaluate a model if we have limited data. To perform CV we need to keep aside a sample/portion of the data which…
Confusion Matrix for Model Selection
Before we jump into calculating Accuracy, Precision, and Recall for our classification model, we first need to understand what a Confusion matrix is. In machine learning, Classification is used to split data into categories. But after cleaning and preprocessing the data and training our model, how do we know if our classification model performs well?…
Gradient Descent (now with a little bit of scary maths)
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Model Selection using R-squared (R²) Measure
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2. Ensemble Learning Methods
“Unity is strength”. This old saying expresses pretty well the underlying idea that rules the very powerful “ensemble methods” . Ensemble methods* are techniques that combine the decisions from several base machine learning (ML) models to find a predictive model to achieve optimum results. This algorithm can be any machine learning algorithm such as logistic…