Which of the following classification algorithms are as follows:
A. Judging whether the tumor is benign or malignant according to the size of the tumor and the age of the patient?
B. according to the user's age, occupation and deposit amount, whether the credit card will default or not is judged?
C. what size t-shirt does a man with a height of 1.85m and a weight of 1kg wear?
D. estimate the house price according to the characteristics such as the size of the house and the number of bathrooms.
correct answer: according to the size of the tumor and the age of the patient, whether it is benign or malignant? ; Judging whether the credit card will default according to the user's age, occupation and deposit amount? ; What size t-shirt does a man with a height of 1.85m and a weight of 1kg wear?
Common classification algorithms:
1. Decision tree: Decision tree is a tree structure used to classify examples. A tree built on strategic choices.
decision trees are composed of node and directed edge. There are two types of nodes: internal nodes and leaf nodes. Among them, the internal node represents the test condition of a feature or attribute (used to separate records with different characteristics), and the leaf node represents a classification.
2. Bayes: Bayes classification algorithm is a kind of algorithm that uses the knowledge of probability and statistics to classify, such as Naive Bayes algorithm. These algorithms mainly use Bayes theorem to predict the possibility that an unknown sample belongs to various categories, and choose the most likely category as the final category of the sample.
because the establishment of Bayesian theorem itself requires a strong conditional independence assumption, which is often not true in practical situations, its classification accuracy will decline.
3. Artificial neural network: Artificial Neural Networks (ANN) is a mathematical model that uses a structure similar to the synapse connection of the brain to process information. In this model, a large number of nodes (or "neurons" or "cells") are connected with each other to form a network, that is, a "neural network" to achieve the purpose of processing information. Neural networks usually need to be trained, and the process of training is the process of learning by networks.