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