Supervised Learning with Python: Concepts and Practical Implementation Using Python

Index

A

AdaBoosting

Akaike information criteria (AIC)

Anaconda-Navigator

Artificial neural networks (ANN)

B

Bagging models

Bag-of-words (BOW) approach

Batch prediction

Bayesian information criteria (BIC)

Bayesian optimization

Bias-variance tradeoff

Binomial distribution

Boosting algorithms

AdaBoosting

definition

final model

gradient boosting

See alsoGradient boosting

SVM

See alsoSupport avector machine (SVM

training dataset

C

CatBoost

Chi-square automatic interaction detection (CHAID)

Classification algorithm

accuracy assessment criteria

applications

credit risk

business context

business objective

dataset

income prediction on census data

k-nearest neighbor

logistic regression

Naïve Bayes

supervised classified algorithms

target variable and independent variables

tree-based algorithms ...