Data Science Dojo

JULY 15, 2024

Support Vector Machines (SVM): This algorithm finds a hyperplane that best separates data points of different classes in high-dimensional space. K-Nearest Neighbors (KNN): This method classifies a data point based on the majority class of its K nearest neighbors in the training data.

Machine Learning 307

Machine Learning Machine Learning Algorithm Clustering 307

Mlearning.ai

FEBRUARY 15, 2023

K-Nearest Neighbou r: The k-Nearest Neighbor algorithm has a simple concept behind it. The method seeks the k nearest neighbours among the training documents to classify a new document and uses the categories of the k nearest neighbours to weight the category candidates [3].

Cross Validation 52

Cross Validation Decision Trees Algorithm Natural Language Processing 52

AWS Machine Learning Blog

FEBRUARY 25, 2025

Instead of treating each input as entirely unique, we can use a distance-based approach like k-nearest neighbors (k-NN) to assign a class based on the most similar examples surrounding the input. To make this work, we need to transform the textual interactions into a format that allows algebraic operations.

Algorithm 71

Algorithm Machine Learning Machine Learning K-nearest Neighbors 71

Towards AI

JULY 19, 2023

(Check out the previous post to get a primer on the terms used) Outline Dealing with Class Imbalance Choosing a Machine Learning model Measures of Performance Data Preparation Stratified k-fold Cross-Validation Model Building Consolidating Results 1. among supervised models and k-nearest neighbors, DBSCAN, etc.,

Machine Learning 40

Machine Learning Machine Learning K-nearest Neighbors Support Vector Machines 40

Pickl AI

JULY 26, 2023

K-Nearest Neighbors with Small k I n the k-nearest neighbours algorithm, choosing a small value of k can lead to high variance. A smaller k implies the model is influenced by a limited number of neighbours, causing predictions to be more sensitive to noise in the training data.

Machine Learning 52

Machine Learning Machine Learning Cross Validation Decision Trees 52

Pickl AI

NOVEMBER 18, 2024

spam detection), you might choose algorithms like Logistic Regression , Decision Trees, or Support Vector Machines. customer segmentation), clustering algorithms like K-means or hierarchical clustering might be appropriate. K-Nearest Neighbors), while others can handle large datasets efficiently (e.g.,

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

Pickl AI

SEPTEMBER 12, 2024

Clustering: An unsupervised Machine Learning technique that groups similar data points based on their inherent similarities. Cross-Validation: A model evaluation technique that assesses how well a model will generalise to an independent dataset.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52