Machine Learning features implementation.

[vsaveris]

Machine learning features implementation progress tracker.

• [x] ML Features Development
• [ ] ML Features Unit Tests Development
• [ ] ML Features Unit Tests Execution
• [ ] ML Features Documentation

[vsaveris]

MachineLearningData class implemented. Concurrency feature is handled by a separate issue (#24). Unit Test cases development should start (issue #25).

Usage example:

import pandas as pd

df = pd.read_csv('sample_data.csv', parse_dates=True, index_col=0)

ml_data = MachineLearningData(
    input_data=df,
    ti_features=[{'ti': 'AccumulationDistributionLine', 'kwargs': {}},
                 {'ti': 'AverageTrueRange', 'kwargs': {}},
                 {'ti': 'BollingerBands', 'kwargs': {'std_number': 3, 'period': 50}}],
    price_diff_periods=1, 
    verbose=True)

data = ml_data.createMLData()

ml_data.saveMLData('ml_data.csv')

[vsaveris]

Concurrency implemented.

Without concurrency, all technical indicators as features: Execution time for all indicators: 203.193 seconds

With concurrency, all technical indicators as features: Execution time for all indicators: 30.831 seconds

[vsaveris]

Machine Learning API development is done.