Bayesian classifier for text classification
Text classification is not only a large module in modern machine learning applications, but also one of the foundations of natural language processing. We can process text data into digital data, and then use Bayes to help us judge a paragraph, or the topic classification, emotional tendency, and eve ...
Posted on Wed, 01 Dec 2021 20:33:05 -0500 by Decipher
SVM was first proposed by Vladimir N. Vapnik and Alexey Ya. Chervonenkis in 1963. The current version (soft margin) was proposed by Corinna Cortes and Vapnik in 1993 and published in 1995. Before the emergence of deep learning (2012), SVM was considered as the most successful and best performing algorithm in machine learning in rec ...
Posted on Sun, 28 Nov 2021 16:59:43 -0500 by czukoman20
The main modules used in this analysis are: numpy, matplotlib, pandas, sklearn.liner_ Lineexpression in model
1. Data reading
The data includes user behavior data and vip user behavior data
2. Data analysis
When we use
After finding that there are no missing values in the code, we start to analyze th ...
Posted on Fri, 26 Nov 2021 16:41:51 -0500 by robsgaming
SVM is a very elegant algorithm with perfect mathematical theory. It is often used in data classification and data regression prediction. Due to its beautiful theoretical guarantee and the processing skills of kernel function for linear inseparable problems, SVM was very popular around the 1990s.
SVM includes the functions of many algorithms: ...
Posted on Wed, 03 Nov 2021 04:13:48 -0400 by whare
sklearn -- Transformer and estimator
Among the sklearn I contacted before, there are SimpleImputer, OrdinalEncoder and OneHotEncoder. What they have in common is that they are all used for data feature preprocessing.
In the use of them, it is inevitable to encounter: fit_transform,transform. At first, I didn't fully understand it, but I ...
Posted on Thu, 28 Oct 2021 20:53:02 -0400 by bulldorc
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