The isotonic regression is used to fit monotonic curve, and classifier calibration is a typical use case.

The isotonic regression is used to fit monotonic curve, and classifier calibration is a typical use case.

Introduction to the random forest decision tree, the gradient boosting regression tree, and the adaptive boosting classification tree.

Introduction to the random forest decision tree, the gradient boosting regression tree, and the adaptive boosting classification tree.

A very rough view on the CART, without the mention of implementation details.

A very rough view on the CART, without the mention of implementation details.

The type I error, the type II error, and some other concepts in the significance test.

The type I error, the type II error, and some other concepts in the significance test.

Basics on combination and permutation.

Basics on combination and permutation.

It is the number of ways to partition a set of objects into non-empty subsets.

It is the number of ways to partition a set of objects into non-empty subsets.

A random experiment, also called the matching experiment.

A random experiment, also called the matching experiment.

The inclusion-exclusion principle is a generalized technique for finding the cardinality of the union of sets.

The inclusion-exclusion principle is a generalized technique for finding the cardinality of the union of sets.

A more detailed view on sign test, which is a statistical method to test for consistent differences between pairs of observations.

A more detailed view on sign test, which is a statistical method to test for consistent differences between pairs of observations.