Predictive Analytics and Data Mining

These flashcards cover key concepts and terminology related to Predictive Analytics and Data Mining, as outlined in the lecture.

Predictive Analytics

The practice of using data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data.

Data Mining

The process of discovering patterns and knowledge from large amounts of data.

CRISP-DM

CRoss-Industry Standard Process for Data Mining; a structured approach for managing data mining projects.

Classification

A data mining task where data is categorized into predefined classes.

Clustering

An unsupervised data mining task that groups similar entities together based on characteristics.

Regression Analysis

A supervised learning technique that predicts a continuous outcome variable based on one or more predictor variables.

Data Preparation Phase

A labor-intensive phase in data mining where raw data is cleaned and transformed for analysis.

Modeling Phase

The phase where appropriate modeling techniques are selected and applied to optimize results.

Evaluation Phase

The phase where the models created are assessed for quality and effectiveness before deployment.

Deployment Phase

The final phase where the models are utilized in real-world applications.