Optimizing the classification prediction of probabilistic neural network PNN based on the cuckoo algorithm – code attached Article directory Classification prediction of probabilistic neural network PNN based on cuckoo algorithm optimization – code attached 1. Overview of PNN network 2. Related background of transformer fault diagnosis system 2.1 Model establishment 3. PNN network based on […]

# Tag: classification

## GJO-LSTM-Adaboost optimizes Adaboost classification prediction of long short-term memory neural network LSTM based on the golden jackal algorithm

?About the author: A Matlab simulation developer who loves scientific research. He cultivates his mind and improves his technology simultaneously. For code acquisition, paper reproduction and scientific research simulation cooperation, please send a private message. Personal homepage: Matlab Research Studio Personal credo: Investigate things to gain knowledge. For more complete Matlab code and simulation customization […]

## Naive Bayes – spam classification

Tip: After the article is written, the table of contents can be automatically generated. For how to generate it, please refer to the help document on the right. Article Directory Preface 1. Bayesian 2. Naive Bayes 3. Code 4. A little self-judgment Summarize Foreword Whether spam has been bothering you, the Bayesian formula gives you […]

## The use and classification of 68 built-in functions in Python

Foreword Functions built into the Python interpreter that can be used directly. These functions require no additional imports or installation and can be called directly from Python code. Python’s built-in functions include many commonly used functions, such as operations on data types, mathematical operations, string processing, file operations, etc. Some common built-in functions include print(), […]

## Data Analysis Practice | Bayesian Classification Algorithm – Automatic Case Diagnosis Analysis

Table of Contents 1. Data and analysis objects 2. Purpose and analysis tasks 3. Methods and Tools 4. Data reading 5. Data understanding 6. Data preparation 7. Model training 8. Model evaluation 9. Model parameter adjustment 10. Model prediction 1. Data and analysis objects CSV file – “bc_data.csv” Dataset link: https://download.csdn.net/download/m0_70452407/88524905 This data set mainly […]

## Preprocessing of YOLOv5 classification model (2) ToTensor and Normalize

Preprocessing of YOLOv5 classification model (2) ToTensor and Normalize flyfish 1. The initial data is a floating point number import torch import numpy as np from torchvision import transforms mean = (0.485, 0.456, 0.406) std = (0.229, 0.224, 0.225) data0 = np.random.random((4, 5, 3)) # H x W x C data0 = np.round(data0,4) print(data0.shape) print(data0) […]

## CS231n-Course Note01-Image Classification with Linear Classifiers

Core Concepts: K-Nearest Neighbor Linear classifiers: SVM, Linear classifiers:Softmax Two-layer neural network Image features As a core task in Computer Vision, Image Classification has two basic data-driven approaches which is K-nearest neighbor and linear classifier. In Machine Learning, the Data-Driven approach can be summarized into three key steps: Collect a dataset of images and labels […]

## Image classification problem based on caltech101

Task description Based on the image classification of the Caltech101 data set, Caltech101 contains 101 categories of objects, each category has about 40 to 800 images, and 16 categories are selected. It is necessary to use an algorithm to identify which category the image belongs to based on the image characteristics. Data description The image […]

## Data classification of BP neural network-speech feature signal classification

Hello everyone, I am taking me to ski! BP neural network, also known as backpropagation neural network, is a type of artificial neural network (ANN) commonly used for classification and regression tasks. It is a feedforward neural network that usually consists of an input layer, one or more hidden layers, and an output layer. The […]

## R Data Analysis: Understanding Net Reclassification (NRI) and Integrated Discriminant Improvement (IDI) Index

Our most common indicator for evaluating the performance of classification prediction models is the ROC curve, which reports AUC. For example, if there are two models, let’s compare the AUCs of the two models to determine the performance of the two models. This is our normal practice. If our research focus is on “Whether the […]