Pickl AI

JANUARY 21, 2025

k-Nearest Neighbors (k-NN) k-NN is a simple algorithm that classifies new instances based on the majority class among its k nearest neighbours in the training dataset. K-Means Clustering K-means clustering partitions data into k distinct clusters based on feature similarity.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

Pickl AI

APRIL 13, 2025

Pattern Recognition and Prediction Classification algorithms excel at recognizing patterns in data, which is crucial for: Predictive Analytics : By learning from historical data, classification models can predict future outcomes. Each instance is assigned to one of several predefined categories.

Machine Learning 52

Machine Learning Machine Learning Decision Trees K-nearest Neighbors 52

IBM Journey to AI blog

DECEMBER 20, 2023

Supervised learning is commonly used for risk assessment, image recognition, predictive analytics and fraud detection, and comprises several types of algorithms. Regression algorithms —predict output values by identifying linear relationships between real or continuous values (e.g., temperature, salary).

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

Dataconomy

APRIL 4, 2023

Some of the common types are: Linear Regression Deep Neural Networks Logistic Regression Decision Trees AI Linear Discriminant Analysis Naive Bayes Support Vector Machines Learning Vector Quantization K-nearest Neighbors Random Forest What do they mean? AI models can be trained to recognize patterns and make predictions.

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Dataconomy

APRIL 4, 2023

Some of the common types are: Linear Regression Deep Neural Networks Logistic Regression Decision Trees AI Linear Discriminant Analysis Naive Bayes Support Vector Machines Learning Vector Quantization K-nearest Neighbors Random Forest What do they mean? AI models can be trained to recognize patterns and make predictions.

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Pickl AI

NOVEMBER 18, 2024

Clustering and dimensionality reduction are common tasks in unSupervised Learning. For example, clustering algorithms can group customers by purchasing behaviour, even if the group labels are not predefined. Predictive analytics uses historical data to forecast future trends, such as stock market movements or customer churn.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52