Meteos/Usecases

Use Cases
Machine Learning consists of the following phases.


 * Learning Phase - Analyze huge amounts of data and create a Prediction Model
 * Evaluation Phase - Evaluate model accuracy
 * Prediction Phase - Predict a value according to the input value by using Prediction Model

Use Case in Learning Phase

 * Upload Raw Data - Upload a raw data to Object Storage
 * Parse Raw Data - Parse a raw data to enable MLllib (Apache Spark's scalable machine learning library) to handle it. Users are allowed to parse the parsed data again.
 * Create Prediction Model - Create a Prediction Model by using MLlib

Use Case in Evaluation Phase

 * Create Dataset for Evaluation
 * Evaluate Model Accuracy
 * Recreate Prediciton Model with new datasets or new parameters

Use Case in Prediction Phase

 * Predict - Input any value and retrieve predicted value