Dataconomy

MARCH 4, 2025

Data mining is a fascinating field that blends statistical techniques, machine learning, and database systems to reveal insights hidden within vast amounts of data. Businesses across various sectors are leveraging data mining to gain a competitive edge, improve decision-making, and optimize operations.

Data Mining 91

Data Mining Data Mining Data Mining Decision Trees 91

Pickl AI

JULY 31, 2023

Examples of Lazy Learning Algorithms: K-Nearest Neighbors (k-NN) : k-NN is a classic Lazy Learning algorithm used for both classification and regression tasks. The algorithm identifies the k-nearest neighbors, where k is a user-defined parameter that is most similar to the new instance.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Algorithm 52

PyImageSearch

JUNE 19, 2023

Recommendation Techniques Data mining techniques are incredibly valuable for uncovering patterns and correlations within data. Figure 5 provides an overview of the various data mining techniques commonly used in recommendation engines today, and we’ll delve into each of these techniques in more detail.

K-nearest Neighbors 56

K-nearest Neighbors Clustering Algorithm Deep Learning 56

Pickl AI

JULY 17, 2023

It aims to partition a given dataset into K clusters, where each data point belongs to the cluster with the nearest mean. It works iteratively by updating cluster centers and reassigning data points until convergence. Unsupervised learning has advantages in exploratory data analysis, pattern recognition, and data mining.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Clustering 52

Pickl AI

SEPTEMBER 12, 2024

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. Introduction In the rapidly evolving field of Data Science, understanding key terminology is crucial for Data Analysts to communicate effectively, collaborate effectively, and drive data-driven projects.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Mlearning.ai

MAY 23, 2023

Once the data is acquired, it is maintained by performing data cleaning, data warehousing, data staging, and data architecture. Data processing does the task of exploring the data, mining it, and analyzing it which can be finally used to generate the summary of the insights extracted from the data.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

Dataconomy

SEPTEMBER 1, 2023

Several data mining and neural network techniques have been employed to gauge the severity of heart disease but the prediction of it is a different subject. Researchers often experiment with various algorithms like random forest, K-nearest neighbor, and logistic regression to find the best combination.

Decision Trees 195

Decision Trees Machine Learning Machine Learning Support Vector Machines 195