advanced-algorithmic-trading

439
#model = LinearDiscriminantAnalysis()
#model = BaggingClassifier(
# base_estimator=DecisionTreeClassifier(),
# n_estimators=n_estimators,
# random_state=random_state,
# n_jobs=n_jobs
#)
#model = GradientBoostingClassifier(
# n_estimators=n_estimators,
# random_state=random_state
#)
model = RandomForestClassifier(
n_estimators=n_estimators,
n_jobs=n_jobs,
random_state=random_state,
max_depth=10
)
model.fit(X_train, y_train)
#model.fit(X, y)
print("Outputting metrics...")
print("Hit-Rate: %s" % model.score(X_test, y_test))
print("%s\n" % confusion_matrix(model.predict(X_test), y_test))
print("Pickling model...")
joblib.dump(model, ’/path/to/your/ml_model_rf.pkl’)
# intraday_ml_strategy.py
import numpy as np
import pandas as pd
from sklearn.externals import joblib
from qstrader.price_parser import PriceParser
from qstrader.event import (SignalEvent, EventType)
from qstrader.strategy.base import AbstractStrategy
class IntradayMachineLearningPredictionStrategy(AbstractStrategy):
"""
Requires:
tickers - The list of ticker symbols