Classification

To predict the category to which a customer belongs to.

To predict whether a customer switches to another provider/brand.

To predict the amount of money a customer will spend in one year.

To predict whether a customer responds to a particular advertising campaign or not.

Logistic regression can be used both for binary classification and multi-class classification

Logistic regression is analogous to linear regression but takes a categorical/discrete target field instead of a numeric one.

In logistic regression, the dependent variable is binary.

The probability that a person has a heart attack within a specified time period using person’s age and sex.

Customer’s propensity to purchase a product or halt a subscription in marketing applications.

Likelihood of a homeowner defaulting on a mortgage.

Estimating the blood pressure of a patient based on her symptoms and biographical data.

kNN is a classification algorithm that takes a bunch of unlabelled points and uses them to learn how to label other points.

kNN algorithm can be used to estimate values for a continuous target.

It is the information that can decrease the level of certainty after splitting in each node.

It is the entropy of a tree before split minus weighted entropy after split by an attribute.

It is the amount of information disorder, or the amount of randomness in each node.

Classification >> Machine Learning with Python