Meteos/Usecases
< Meteos
Contents
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