Classification Or Categorical

Classification is basically a technique where we classify data into a number of classes based on certain features. There are a number of classification models. Classification models include logistic regression, decision tree, random forest, gradient-boosted tree, multilayer perceptron, one-vs-rest, and Naive Bayes. For example you want to filter your emails as spam or not spam or split a group of people based on their genders,the model used is a classification model.

linear models give us the same output for a given data over and over again. Whereas, machine learning models, irrespective of classification or regression give us different results.

Machine Learning Models have to reach a higher level of accuracy in their predictions and they are also called Artificial Intelligence Models. We can differentiate them into two parts- Discriminative algorithms and Generative algorithms. 

• text categorization (e.g., spam filtering)

• fraud detection

• optical character recognition • machine vision (e.g., face detection)

• natural-language processing (e.g., spoken language understanding)

• market segmentation (e.g.: predict if customer will respond to promotion)

• bioinformatics (e.g., classify proteins according to their function)

are a few examples of CLASSIFICATION MODELS.