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Feature selection and feature learning of "feature engineering"

http://www.jianshu.com/p/ab697790090fFeature selection and feature learningIn the practical task of machine learning, it is very important to select a set of representative features for building the model. Feature selection typically chooses a

Foundation of Image Processing-geometric significance of feature vectors

Geometric significance of feature vectors   For a long time, I have never understood the significance of the matrix feature values and feature vectors (it is estimated that many of them feel the same way ). I know its mathematical formula, but I can'

Feature value and feature vector: Application in signal processing

I have Reprinted from others and analyzed the functions of feature values and feature vectors. After reading the article, I suddenly realized that I admire the author's pen and depth. Original Author link: http://www.douban.com/note/129544864/ [1.

Review of data cleansing and feature processing in machine learning

A survey of data cleansing and feature processing in machine learning with the increase of the size of the company's transactions, the accumulation of business data and transaction data more and more, these data is the United States as a group

Machine Learning-feature selection Feature Selection Research Report

Note: I wrote this report in December, (first year of doctor's degree). I recently reviewed my computer and summarized the report when I was learning about paper on KDD, now let's share it with you. After all, I wrote it when I was a beginner, and

Haowen! Geometric and physical meanings of feature values and feature vectors]

We know that matrix multiplication corresponds to a transformation, which converts any vector into a new vector with different directions or lengths. During this transformation, the original vector mainly changes in rotation and scaling. If a matrix

Feature Engineering-Feature Selection

Feature Engineering is part of the most time-and effort-consuming work in data analysis. It is not just a definite step like algorithms and models, but also engineering experience and trade-offs. Therefore, there is no uniform method. Here is just a

Continuous feature discretization achieves better results, and the engineering method of feature selection

http://www.zhihu.com/question/31989952Discretization of continuous features: Under what circumstances will continuous features be discretized to achieve better results?Q:CTR estimates that CTR estimates are generally used in LR, and that the

Physical significance of feature vectors (PCA) -- Post

What is feature vector, feature value, matrix decomposition? [1. mathematical significance of features]First, we examine a linear change. For example, the elliptic equation in the X and Y coordinate systems can be written as x ^ 2/A ^ 2 + y ^ 2/B ^ 2

Physical significance of High-number feature vectors

[1. mathematical significance of features]First, we examine a linear change. For example, the elliptic equation in the X and Y coordinate systems can be written as x ^ 2/A ^ 2 + y ^ 2/B ^ 2 = 1, after the coordinate system rotates the origin, the

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