GitHub

Max-Eisman/Python-Hw-10

IMPORTANT NOTE: There will be no late submissions for HW 10 (i.e., any submission past the deadline will recieve a grade of 0). This homework asks you to fill in portions of code to classify an image ...
Design News

How to Build an Arduino-Based Solar Power Prediction System Using Python & Machine Learning, Part 2

In this tutorial, we’ll build on the foundation laid in the “Arduino-Based Solar Power System Using Python & Machine Learning, Part 1” project by exploring how to intelligently select and use machine ...
Nature

RETRACTED ARTICLE: Comparative analysis of heart disease prediction using logistic regression, SVM, KNN, and random forest with cross-validation for improved accuracy

This primary research paper emphasizes cross-validation, where data samples are reshuffled in each iteration to form randomized subsets divided into n folds. This method improves model performance and ...
Scientific Research Publishing

Research on Vehicle Tracking Method Based on YOLOv8 and Adaptive Kalman Filtering: Integrating SVM Dynamic Selection and Error Feedback Mechanism ()

1 School of Computer Science, Sichuan University Jinjiang College, Meishan, China. 2 School of Automotive and Transportation, Xihua University, Yibin, China. Vehicle tracking plays a crucial role in ...
IEEE

Implementation of ML Algorithm for Spyware Detection System Using SVM with KNN Algorithm for Comparison of Accuracy

Abstract: The research examines the Support Vector Machines (SVM) and K-Nearest Neighbor (KNN) machine learning algorithms with the goal of using machine learning to detect malware and mitigate ...
IEEE

Buried Magnetic Material Detection System: An SVM Algorithm Application

Abstract: In recent times, studies about remote-sensing methods have focused on improving variables like sensing distance, sensitivity, and power consumption of available remote-sensing methods. The ...
Nature

Construction of power network security risk assessment model based on LSA-SVM algorithm in the background of smart grid

Due to theintricate and interdependent nature of the smart grid, it has encountered an increasing number of security threats in recent years. Currently, conventional security measures such as ...
LinkedIn

Hyperparameter Tuning with GridSearchCV: A Hands-On Example with SVM and the Iris Dataset

Hyperparameter tuning is a critical step in optimizing machine learning models for optimal performance. It involves selecting the best combination of hyperparameters, such as regularization strength, ...
Frontiers

Supervised machine learning models for depression sentiment analysis

Globally, the prevalence of mental health problems, especially depression, is at an all-time high. The objective of this study is to utilize machine learning models and sentiment analysis techniques ...
Scientific Research Publishing

Pedregosa, F., Varoquaux, G., Gramfort, A., et al. (2011) Scikit-Learn: Machine Learning in Python. Journal of Machine Learning Research, 12, 2825-2830.

ABSTRACT: The manuscript presents an augmented Lagrangian—fast projected gradient method (ALFPGM) with an improved scheme of working set selection, pWSS, a decomposition based algorithm for training ...