Machine Learning (Theory)

MARCH 5, 2025

Support Vector Machines were disrupted by deep learning, and convolutional neural networks were displaced by transformers. As an example, the speech recognition community spent decades focusing on Hidden Markov Models at the expense of other architectures, before eventually being disrupted by advancements in deep learning.

AI 157

AI AI Support Vector Machines Deep Learning 157

Pickl AI

APRIL 13, 2025

Examples include: Spam vs. Not Spam Disease Positive vs. Negative Fraudulent Transaction vs. Legitimate Transaction Popular algorithms for binary classification include Logistic Regression, Support Vector Machines (SVM), and Decision Trees. These models can detect subtle patterns that might be missed by human radiologists.

Machine Learning 52

Machine Learning Machine Learning Decision Trees K-nearest Neighbors 52

Flipboard

JULY 4, 2025

More On This Topic Principal Component Analysis (PCA) with Scikit-Learn A Gentle Introduction to Rust for Python Programmers A Gentle Introduction to Go for Python Programmers A Gentle Introduction to Support Vector Machines A Gentle Introduction to Symbolic AI Introduction to Python Libraries for Data Cleaning Our Top 5 Free Course Recommendations (..)

Python 132

Python Natural Language Processing Machine Learning Data Science 132

Flipboard

JULY 10, 2025

However, the combination of EfficientNetB0 pre-training with ML Support Vector Machines (SVM) produced optimal results with accuracy, sensitivity, specificity, precision, F1-Score, and AUC, of 99.4%, 98.7%, 99.1%, 99%, 98.8%, and 100%, respectively. This work employed and tested a variety of pre-training and ML techniques.

Support Vector Machines 81

Support Vector Machines ML ML Machine Learning 81

Pickl AI

JANUARY 12, 2025

Develop Hybrid Models Combine traditional analytical methods with modern algorithms such as decision trees, neural networks, and support vector machines. Clustering algorithms, such as k-means, group similar data points, and regression models predict trends based on historical data.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence AI AI 52

Pickl AI

JUNE 12, 2025

Support Vector Machines (SVMs): Parameters include the weights defining the hyperplane that separates classes. Neural Networks: Parameters include weights and biases for each neuron connection. These parameters determine how input features are transformed through layers to produce outputs.

Machine Learning 52

Machine Learning Machine Learning Algorithm Support Vector Machines 52

Pickl AI

FEBRUARY 2, 2025

Comparison with Other Classification Techniques Associative classification differs from traditional classification methods like decision trees and support vector machines (SVM). The computational cost and complexity of implementing associative classification in large-scale operations can pose significant challenges.

Data Mining 52

Data Mining Data Mining Data Mining Decision Trees 52

Pickl AI

APRIL 6, 2025

Helping Algorithms Like SVM Support Vector Machines ( SVM ) are popular machine learning tools that work well with kernel methods. Frequently Asked Questions What are kernel methods in machine learning? Kernel methods solve this by lifting the data into a new space where it becomes easier to separate.

Machine Learning 52

Machine Learning Machine Learning Support Vector Machines Data Science 52

Dataconomy

APRIL 8, 2025

Among the most significant models are non-linear models, support vector machines, and linear regression. Support vector machines (SVM) Support Vector Machines are a robust classification technique in machine learning.

Data Science 91

Data Science Support Vector Machines Data Scientist Data Visualization 91

How to Learn Machine Learning

JULY 6, 2025

Some examples of supervised algorithms are linear regression, logistic regression, support vector machines, and decision trees. Support Vector Machines (SVM): SVMs find the optimal boundary that separates classes in the data, often used for high-dimensional datasets.

Machine Learning 52

Machine Learning Machine Learning Algorithm Clustering 52

Dataconomy

APRIL 29, 2025

Support vector machine (SVM) Support vector machines excel in high-dimensional spaces, making them suitable for complex classification tasks. Its simplicity and interpretability make it a popular choice, particularly in fields requiring clear explanations of predictive relationships.

Support Vector Machines 91

Support Vector Machines Machine Learning Machine Learning Algorithm 91

Pickl AI

JANUARY 21, 2025

Support Vector Machines (SVM) SVMs are powerful classification algorithms that work by finding the hyperplane that best separates different classes in high-dimensional space. Commonly used algorithms include Support Vector Machines, Random Forests, and Gradient Boosting methods; however, selection should be based on testing.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

Dataconomy

MARCH 6, 2025

Common types of surrogate models Surrogate modeling encompasses various machine learning methodologies, including: Polynomial regressions: Useful for capturing relationships in a straightforward manner. Support vector machines: Effective in high-dimensional spaces and can handle nonlinearities.

Support Vector Machines 91

Support Vector Machines Machine Learning Machine Learning Data Science 91

Dataconomy

APRIL 4, 2025

Support vector machines: SVMs employ convex optimization to find the optimal hyperplane that classifies data into two categories. Common applications Portfolio optimization: In finance, convex optimization models help in selecting the best combination of assets to maximize returns while minimizing risk.

Machine Learning 91

Machine Learning Machine Learning Support Vector Machines Algorithm 91

AWS Machine Learning Blog

FEBRUARY 25, 2025

Classification algorithms like support vector machines (SVMs) are especially well-suited to use this implicit geometry of the data. The previous visualization of the embeddings space displayed only a 2D transformation of this space. This doesnt imply that clusters coudnt be highly separable in higher dimensions.

Algorithm 81

Algorithm Machine Learning Machine Learning K-nearest Neighbors 81

Flipboard

JULY 20, 2025

This work aims to assess the performance of numerous combinations of machine learning methods to detect alpha and beta-thalassemia in their minor and major types. The analyzed models are K-nearest Neighbor (KNN), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost).

K-nearest Neighbors 81

K-nearest Neighbors Machine Learning Machine Learning Support Vector Machines 81

Dataconomy

APRIL 29, 2025

Support vector machine (SVM) SVM functions as both a classification and regression tool, utilizing the concept of margins and kernels to optimize performance. Pros: Offers clear quantitative insights and is easy to implement. Cons: Susceptible to model dependency and may exhibit limited flexibility with complex data patterns.

Algorithm 91

Algorithm Support Vector Machines Data Analysis Data Analysis 91

Dataconomy

MARCH 25, 2025

Applications of hyperplanes in machine learning Hyperplanes play a critical role in various machine learning algorithms, ranging from classification to clustering and regression. Understanding supporting hyperplanes further enriches the concept of hyperplanes and their role in machine learning.

Support Vector Machines 91

Support Vector Machines Machine Learning Machine Learning Clustering 91

Dataconomy

MARCH 25, 2025

Learning the decision boundary Machine learning algorithms learn decision boundaries through a training process that adjusts the model’s parameters based on the input data. Algorithms like logistic regression or support vector machines focus on optimizing the decision boundary to minimize misclassification errors.

Support Vector Machines 91

Support Vector Machines Machine Learning Machine Learning Clustering 91

Flipboard

JULY 2, 2025

To enhance predictive accuracy, machine learning models Linear Regression, Random Forest Regression, Support Vector Machines (SVM), K-Means Clustering, and Artificial Neural Networks (ANN) were employed to analyze combustion-induced degradation trends, confirming Test-06 as the optimal balance of stability and high performance.

Machine Learning 65

Machine Learning Machine Learning Support Vector Machines Clustering 65

Dataconomy

APRIL 16, 2025

Support Vector Machines: A method that finds the hyperplane separating different classes with the largest margin. Logistic Regression: A statistical method for binary classification that models the probability of a class based on input features.

Supervised Learning 91

Supervised Learning Decision Trees Algorithm Machine Learning 91

NYU Center for Data Science

APRIL 30, 2025

Rico Angell (CDS Postdoctoral Researcher) Monitoring LLM Agents for Sequentially Contextual Harm (Building Trust WorkshopPaper) Sam Bowman (CDS Associate Professor of Linguistics and Data Science) Language Models Learn to Mislead Humans via RLHF (Poster) Inverse Scaling: When Bigger Isnt Better (Poster) Beyond the Imitation Game: Quantifying (..)

Computer Science 54

Computer Science Computer Science Data Science Supervised Learning 54

How to Learn Machine Learning

MARCH 25, 2025

Some common supervised learning algorithms include decision trees, random forests, support vector machines, and linear regression. Algorithms Used in Supervised vs Unsupervised Learning Supervised learning relies on well-known algorithms that help in classification and regression tasks.

Supervised Learning 59

Supervised Learning Machine Learning Machine Learning Algorithm 59

Analytics Vidhya

JUNE 19, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction In this article, we will be discussing Support Vector Machines. The post Support Vector Machine: Introduction appeared first on Analytics Vidhya.

Support Vector Machines 372

Support Vector Machines Data Science Analytics Analytics 372

Dataconomy

FEBRUARY 26, 2025

Machine learning methods: Methods like decision trees, neural networks, and support vector machines, each utilize specific algorithms to identify patterns in datasets. Business ventures: Startups increasingly leverage pattern recognition, creating innovative solutions in various sectors.

Support Vector Machines 91

Support Vector Machines Machine Learning Machine Learning Decision Trees 91

Analytics Vidhya

OCTOBER 12, 2021

This article was published as a part of the Data Science Blogathon Introduction to Support Vector Machine(SVM) SVM is a powerful supervised algorithm that works best on smaller datasets but on complex ones. The post Support Vector Machine(SVM): A Complete guide for beginners appeared first on Analytics Vidhya.

Support Vector Machines 373

Support Vector Machines Data Science Algorithm Analytics 373

Analytics Vidhya

FEBRUARY 3, 2023

Introduction Support vector machines are one of the most widely used machine learning algorithms known for their accuracy and excellent performance on any dataset.

Support Vector Machines 337

Support Vector Machines Algorithm Machine Learning Machine Learning 337

Analytics Vidhya

NOVEMBER 27, 2020

The post Understanding Naïve Bayes and Support Vector Machine and their implementation in Python appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon. Introduction In this digital world, spam is the most troublesome challenge that.

Support Vector Machines 383

Support Vector Machines Python Data Science Analytics 383

Analytics Vidhya

JUNE 5, 2022

Later, we will discuss the Maximal-Margin Classifier and Soft Margin Classifier for Support Vector Machine. The post Support Vector Machine with Kernels and Python Iterators appeared first on Analytics Vidhya. At last, we will learn about some SVM Kernels, such as Linear, Polynomial, and […].

Support Vector Machines 331

Support Vector Machines Python Data Science Analytics 331

Analytics Vidhya

JUNE 16, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Support Vector Machine (SVM) is one of the Machine Learning. The post The A-Z guide to Support Vector Machine appeared first on Analytics Vidhya.

Support Vector Machines 300

Support Vector Machines Machine Learning Machine Learning Data Science 300

Machine Learning Mastery

NOVEMBER 21, 2023

The Support Vector Machine algorithm is one of the most popular supervised machine learning techniques, and it comes implemented in the OpenCV library. This tutorial will introduce the necessary skills to start using Support Vector Machines in OpenCV, using a custom dataset that we will generate.

Support Vector Machines 268

Support Vector Machines Machine Learning Machine Learning Algorithm 268

Dataconomy

MARCH 28, 2025

Gradient boosting machines (GBM): Sequentially builds decision models to enhance predictive power. Support vector machines (SVM): Focuses on class separation through hyperplanes. Random forests: An ensemble technique utilizing multiple trees for improved stability and accuracy.

Decision Trees 91

Decision Trees Support Vector Machines Machine Learning Algorithm 91

KDnuggets

MARCH 18, 2020

Support Vector Machines (SVMs) are powerful for solving regression and classification problems. You should have this approach in your machine learning arsenal, and this article provides all the mathematics you need to know -- it's not as hard you might think.

Support Vector Machines 321

Support Vector Machines Machine Learning Machine Learning Algorithm 321

Analytics Vidhya

JUNE 3, 2022

Introduction Classification problems are often solved using supervised learning algorithms such as Random Forest Classifier, Support Vector Machine, Logistic Regressor (for binary class classification) etc. The post One Class Classification Using Support Vector Machines appeared first on Analytics Vidhya.

Support Vector Machines 297

Support Vector Machines Supervised Learning Data Science Algorithm 297

Analytics Vidhya

OCTOBER 6, 2021

Ever wondered, how great would it be, if we could predict, whether our request for a loan, will be approved or not, simply by the use of machine learning, from the ease and comfort […]. The post Loan Status Prediction using Support Vector Machine (SVM) Algorithm appeared first on Analytics Vidhya.

Support Vector Machines 322

Support Vector Machines Algorithm Machine Learning Machine Learning 322

Analytics Vidhya

OCTOBER 23, 2020

The post The Mathematics Behind Support Vector Machine Algorithm (SVM) appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon. Introduction One of the classifiers that we come across while learning about.

Support Vector Machines 298

Support Vector Machines Algorithm Data Science Analytics 298

KDnuggets

SEPTEMBER 12, 2019

This article explains the Support Vector Machines (SVM) algorithm in an easy way.

Support Vector Machines 282

Support Vector Machines Algorithm Machine Learning Machine Learning 282