Decision tree is the basic building block of gradient elevator and random forest. Visual decision tree is very helpful in learning the working principle and interpretability of these models. However, the current visualization package is still very rudimentary and does not help novices much.
When I visited Github recently, I found a great dtree ...
Posted by stallingjohn on Mon, 06 Dec 2021 11:47:30 -0800
KNN, namely k-nearest neighbor method, is a basic classification and regression method proposed by Cover T and Hart P in 1967. It is also one of the basic algorithms of machine learning.
This article's reference tutorial: Machine learning practice
Principle of KNN algorithm
In a sample data set, also known as the training sample set, and eac ...
Posted by compbry15 on Sun, 05 Dec 2021 20:11:28 -0800
Positive samples: samples belonging to a certain class (generally the desired class). In this case is a passing student.Negative samples: samples that do not belong to this category. In this case, it is a failed student.
y_pred = [0, 0, 0, 0, 0, 0, 1, 1, 1, 1] y_true = [0, 0, 0, 0, 1, 1, 1, 1, 0, 0]
The above 0 represents failure ...
Posted by DaRkZeAlOt on Sun, 05 Dec 2021 18:01:20 -0800
1.Autograd (automatic gradient algorithm)
autograd is the core package of PyTorch to implement the automatic gradient algorithm mentioned earlier. Let's start by introducing the variables.
autograd.Variable is the encapsulation of Tensor. Once we have defined the final variable (i.e., calculated loss, etc.), we can call its backwa ...
Posted by csxpcm on Sun, 05 Dec 2021 15:57:54 -0800
1) ID number
2) Diagnosis (M = malignant, B = benign)
Calculate 10 real value characteristics of each nucleus:
a) Radius (average distance from center to perimeter)
b) Texture (standard deviation of gray value)
e) Smoothness (local variation of radius length)
f) Compactness (perimeter ^ ...
Posted by ajlisowski on Sun, 05 Dec 2021 02:35:38 -0800
Hello, everyone. Today, I'd like to share with you the derivation process of forward propagation in tensorflow 2.0 deep learning, using the mnist data set provided by the system.
1. Data acquisition
First, we import the required library files and datasets. The imported x and y data are array types and need to be converted to tensor type tf.co ...
Posted by djw821 on Sun, 05 Dec 2021 01:44:16 -0800
Data parameters OrderNumber: customer nickname LineNumber: purchase order. For example, the first three lines respectively represent three goods purchased by the same customer Model: trade name
Application of intelligent algorithm recommendation of association rules based on shopping basket.
Three basic ...
Posted by Skara on Sat, 04 Dec 2021 22:41:39 -0800
This blog focuses on the most important code in the entire training or prediction code because it initializes the loading of all other models, data processing visualization, log printing, and so on.
Before introducing these classes, let's briefly summarize the five main categories of Framework:
Learner: The mai ...
Posted by Nilanka on Sat, 04 Dec 2021 09:51:15 -0800
As we all know, we brush questions before the exam. But most of the exams are not the original questions. What's the use of brushing questions before the exam? Of course, as like as two peas, we did not want to have the same questions in the exam. (maybe. In fact, in machine learning, the questions brushed before the test are the ...
Posted by emopoops on Thu, 02 Dec 2021 21:34:25 -0800