This kind of thinking underlies the ID3 algorithm for learning decisions trees, which we will describe more formally below. However, the reasoning is a little more subtle, as ... As we discussed in ...

Other common machine learning regression algorithms (short of neural networks) include Naive Bayes, Decision Tree, K-Nearest Neighbors, LVQ (Learning Vector Quantization), LARS Lasso, Elastic Net ...

In this online data science specialization, you will apply machine learning algorithms to real-world data, learn when to use which model and why, and improve the performance of your models. Beginning ...

A decision tree is a machine learning technique that can be used for binary classification or multi-class classification. ... After the first split, the decision tree algorithm examines each of the ...

For decision tree classification, the variable to predict is most often ordinal-encoded (0, 1, 2 and so on) The numeric predictors do not need to be normalized to all the same range -- typically 0.0 ...