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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 ...

1. Source code modification (1) Error reporting UnicodeDecodeError: 'gbk' codec can't decode byte 0x9a in position 8: illegal multibyte sequence   Load ../data/PHP-WEBSHELL/xiaoma/1148d726e3bdec6db65db30c08a75f80.php Traceback (most recent call last): ...... t=load_file(file_path) for line in f: UnicodeDecodeError: 'gbk' codec can't deco ...

brief introduction Using Pandas's pivot method, DF can be rotated and transformed. This paper will explain the secret of pivot in detail. Using Pivot pivot is used to reorganize the DF, and use the specified index, columns and values to reconstruct the existing DF. Take a Pivot example: Through pivot change, the new DF uses the value ...

Author: baiyucraft BLog: baiyucraft's Home Original text: Hands on learning and deep learning 1, Differential and derivative    I believe everyone knows the concept. Draw a picture according to the book: import numpy as np from matplotlib import pyplot as plt def set_figsize(figsize=(3.5, 2.5)): """set up matplotlib The ...

ROS learning notes (II) file system Opening: file system structure of ROS. To learn to build a ROS project, we must first understand a ROS project, understand their organizational structure, be fundamentally familiar with the organizational form of ROS project, and understand the functions and functions of various documents, so as to carry out ...

The original paper is: "Pattern Classification with Corrupted Labeling via Robust Broad Learning System" The idea of GRBLS: The aforementioned BLS models are based on the mean square error (MSE) criterion to fit the approximation errors [23]. In fact, MSE aims to measure the sum of quadratic loss of data, and the approximation re ...

RFM user value model 1 demand Assuming I am a marketer, I might think about the following questions before doing an activityWho are my more valuable customers?Who has the potential to become a valuable customer?Who's losing?Who can stay?Who cares about this event?In fact, all the above thoughts focus on one theme valueRFM is one of the most ...

catalogue 1. Basic definitions 2. Algorithm principle 2.1 advantages and disadvantages of the algorithm 2.2 algorithm parameters 2.3 variants 3. Distance formula in the algorithm 4. Case realization 4.1 import related libraries 4.2 reading data 4.3 read variable name 4.4 define X,Y data 4.5 separate training set and test set 4.6 ca ...

When support vector machine makes decision, the selected decision boundary needs to meet a condition, that is, the distance from the nearest point in the two classifications is the longest. It can also be understood that when we use support vector machine for classification, what we need to do is to maximize the distance between the decision bo ...

introduce Machine learning is a method to solve problems that cannot be clearly coded, such as classification problems. The machine learning model will learn a pattern from the data, so we can use it to determine which class the data belongs to. But there's a problem. How does this model work? Some people cannot accept a model with good perfo ...