Programmer Think

Random forest Random forest is a supervised learning algorithm, which is an integrated learning algorithm based on decision tree. Random forest is very simple, easy to implement, and the computational cost is very small. It shows amazing performance in classification and regression. Therefore, random forest is known as "a method represen ...

(1) What is SLAM?    in short, slam is to locate and pose the robot where GPS cannot be used, build incremental maps, and realize the autonomous positioning and navigation of the robot. Like a blind man, he explores the environment with his own hands in the unknown environment, and constantly corrects the map built by his heart to th ...

1, Problem description In the actual daily life, people often encounter the following problems: find the function in a given definition field X f ( x ) f(x) The optimal value corresponding ...

1, Brief introduction of handwritten capital letter recognition technology 0 Introduction In the teaching process of colleges and universities, examination is the most common teaching means of teaching evaluation and comprehensive practice. With the progress of science and technology, the way of examination marking has also undergone great cha ...

LPA(Label Propagation Algorithm) LPA algorithm was proposed by zhu et al in 2002. In 2007, it was applied to the field of community discovery by Usha, Nandini and Raghavan, and RAK algorithm was proposed. But most researchers call RAK algorithm LPA algorithm. LPA is a local community division based on Label Propagation. For each node in the n ...

Summary This is a series of pytorch notes that follow station b. There are a lot of classified articles about renet model image recognition on the internet, but the image part is usually just a link to it. Or read a well-known article and prepared the dataset from scratch. One dataset preparation The dataset consists of 102 categories of flo ...

Parameter setting There are often problems in XGB classification There are parameters to adjust the sample imbalance scale_pos_weight ， Usually, we enter the ratio of negative sample size to positive sample size in the parameter Classification case Create unbalanced dataset import numpy as np import xgboost as xgb im ...

Pretreatment Before starting machine learning, it is often helpful to observe more data in the data set. For example, in the following email We can see a URL, an email address (at the end), numbers and dollar amounts. Although many e-mail messages contain similar types of text (for example, numbers, other URL s, or other e-mail addresse ...

Multiple Features Multiple linear regression, which includes multiple variables, such as house age, area, number of rooms, etc., is marked as follows: Suppose the function becomes: It can be understood as: θ 0 means base price θ 1 is the price per square meter, and X1 is the number of square meters θ 2 is the price of each ...

Training data generation Detailed step reference Modification of configuration file This article takes the human hand detection as an example (there is only one label: hand) Add or modify data / hand Names file, which records labels, one label per line (Note: labels corresponding to training data)Add or modify CFG / hand Data file, the cont ...