1. Experimental contents
This experiment learns and implements the decision tree algorithm.
2. Experimental objectives
Through this experiment, master the basic principle of decision tree algorithm.
3. Experimental knowledge points
Shannon entropyinformation gain
4. Experimental environment
5. Pr ...
Posted on Tue, 12 Oct 2021 19:57:50 -0400 by JasonHarper
python final exam requires a feature extraction project. Today I'll show my results
import numpy as np
# Linear discriminant analysis is imported from sklearn's linear analysis library, that is, LDA maximizes the coordinate axis of inter class discrimination to reduce the dimension of classification preprocessing
from sklear ...
Posted on Mon, 11 Oct 2021 00:09:10 -0400 by mattcass
Principle of Kmeans clustering method: 1. Firstly, K clustering centers are randomly determined; 2. Calculate the distance (Euclidean distance) from each point in the data to the K cluster centers, and classify the point into which cluster which is the smallest; 3. Calculate the center points of all points in each cluster (the corresponding ele ...
Posted on Sat, 09 Oct 2021 15:29:58 -0400 by sitestem
·Introduction to Word2Vec
One of the core concepts of natural language processing is how to quantify words and expressions so that they can be used in the model environment. This mapping of language elements to numerical representations is called word embedding.
Word2Vec is a word ...
Posted on Sat, 09 Oct 2021 14:00:40 -0400 by aspekt9
Iris data set is a classic small-scale data set in machine learning. Through the following experiments, access to materials and videos for learning, share the learning experience and experimental process of the whole experiment, hoping to provide help to novices who love machine learning and get started, and urge themselves to move forward stea ...
Posted on Thu, 07 Oct 2021 17:47:22 -0400 by Lashiec
6_ Gradient Descent method
Gradient descent method is an important search strategy in the field of machine learning. In this chapter, we will explain the basic principle of the gradient descent method in detail, and improve the gradient descent algorithm step by step, so that we can understand the significance of various parameters in the grad ...
Posted on Mon, 04 Oct 2021 18:55:37 -0400 by Duke555
1, K-nearest neighbor algorithm
KNN is a supervised learning class algorithm. Its full name (k-nearest neighbor) is translated into k nearest neighbors. It is a clustering algorithm. The algorithm believes that we can judge the category of an object according to the category of K objects that ar ...
Posted on Sun, 03 Oct 2021 23:47:49 -0400 by gaogier
What is CART?
CART is the abbreviation of Classification And Regression Tree in English, also known as classification regression tree. From its name we can We can see that it is a very powerful algorithm, which can be used not only for classification but also for regression, so it is very worth learning.
CART algorithm uses bi ...
Posted on Sun, 03 Oct 2021 17:53:35 -0400 by diddy1234
Filtering methods are faster but coarser. Packaging and embedding methods are more precise and more suitable for adjustment to algorithms, but they are computationally intensive and take longer to run. When there is a large amount of data, differential filtering and mutual information methods are preferred before other feature ...
Posted on Sun, 03 Oct 2021 13:10:42 -0400 by FireyIce01
1, Summary of learning points
Information obtained from competition informationRead dataEvaluation and calculation of classification indexOn parity calculation of regression indexUnderstanding of some nouns
2, Learning content:
1. New knowledge learned from the competition
a. Desensitization: process some private information, such as 186 ...
Posted on Fri, 01 Oct 2021 19:35:04 -0400 by davidguz