Random forest notes

Random forest Random forest is a supervised learning algorithm, which is an integrated learning algorithm based on decision tree. Random forest is very simple, easy to implement, and the computational cost is very small. It shows amazing performance in classification and regression. Therefore, random forest is known as "a method represen ...

Posted by generic on Sun, 06 Feb 2022 07:45:17 +0100

Implementation of decision tree algorithm by Golang

1, Algorithm Introduction    Decision Tree is a decision analysis method to obtain the probability that the expected value of net present value is greater than or equal to zero, evaluate the project risk and judge its feasibility by forming a Decision Tree on the basis of knowing the occurrence probability of various situations. It i ...

Posted by anler on Mon, 31 Jan 2022 09:13:32 +0100

Supervised algorithm decision tree

Supervised algorithm decision tree 1: Algorithm overview Decision tree: includes classification tree / regression tree. Regression tree is rarely used, so classification tree is mainly introduced here Algorithm flow: feature selection – > decision tree generation – > decision tree pruning 2: Feature selection 2.1 aroma ...

Posted by FraggleRock on Sat, 25 Dec 2021 06:28:28 +0100

Decision tree based on machine learning

Decision tree is a basic classification and regression method 1, Basic concepts of decision tree The nodes and directed edges of the decision tree are represented respectively: An internal node represents a feature or attributeLeaf nodes represent a classification.A directed edge represents a partition rule The directed edge of the decisio ...

Posted by boombanguk on Sat, 18 Dec 2021 18:10:27 +0100

Machine learning: house price forecasting

Return to actual house price forecast Use what you have learned to solve real-world problems. Let's use these principles to estimate house prices. Housing valuation is one of the most classic cases to understand regression analysis, which is usually a good entry point. It is in line with people's intuition and with people Our lives are clos ...

Posted by Fakcon on Thu, 16 Dec 2021 12:23:11 +0100

Other machine learning technologies: decision tree, anomaly detection, PCA

catalogue 1, Definitions and formulas 1. Decision tree 2. Anomaly Detection 3. Principal component analysis PCA 2, Code practice 1. Decision tree: Iris iris Iris data classification 2. Anomaly detection 2.1} visualize the probability density function of Gaussian distribution 2.2} establish a model to realize the prediction of abnormal ...

Posted by kliopa10 on Fri, 10 Dec 2021 11:52:16 +0100

Iris data classification using decision tree algorithm

Iris data classification using decision tree algorithm (learning notes) Introduction to decision tree algorithm The process of building a tree Starting from the root node, calculate the information gain (information gain ratio and Gini coefficient) of all eigenvalues, and select the feature with the largest calculation result as the root ...

Posted by Cheap Commercial on Wed, 08 Dec 2021 00:54:45 +0100

Decision tree of machine combat

1, Introduction 1.1 concept As shown in the figure, it is a decision tree. The square represents the decision block and the ellipse represents the terminating block, indicating that the conclusion has been reached and the operation can be terminated. The left and right arrow branch es are led out from the judgment module, which c ...

Posted by csudhoff on Wed, 27 Oct 2021 17:59:07 +0200

Principle and sklearn implementation of decision tree in machine learning

1. General 1.1 how does the decision tree work? Decision Tree is a nonparametric supervised learning method. It can summarize decision rules from a series of characteristic and labeled data, and present these rules with the structure of tree view to solve the problems of classification and regression. Decision Tree algorithm is easy to unders ...

Posted by Darkmatter5 on Sun, 05 Sep 2021 04:20:17 +0200

[sklearn] 1. Classification decision tree

preface Decision tree is a common algorithm in machine learning. Relevant mathematical theories I also wrote in the column of mathematical modeling Mathematical modeling learning notes (XXV) decision tree Yes, this blog post does not pay attention to the relevant mathematical principles, but mainly focuses on the effect of using sklearn to re ...

Posted by scm24 on Fri, 03 Sep 2021 20:05:40 +0200