Python ModelTrainer Examples

Example #1

File: train_model.py Project: BeccaMayers/model-stacking-workbench

# -*- coding: utf-8 -*-
#%%
from framework.model_stacking import ModelTrainer, ModelPerformanceTracker
from sklearn.neural_network import MLPClassifier as ThisModel

#%%
#
# Set up model for training
#
this_model = ModelTrainer(
    ModelClass=ThisModel,  #Model algorithm
    model_params=dict(hidden_layer_sizes=(50, 25, 10)),  #hyper-parameters
    model_id='L1NN1',  # Model Identifier
    feature_set='L1FS01'  # feature set to use
)

model_tracker = ModelPerformanceTracker(model_trainer=this_model)
#%%
#
# clear out old results
#
this_model.cleanPriorResults()

#%%
#
# train model on all the data
#
this_model.trainModel()

#%%
# create Test predictions

Example #2

File: train_model.py Project: BeccaMayers/model-stacking-workbench

# -*- coding: utf-8 -*-
#%%
from framework.model_stacking import ModelTrainer, ModelPerformanceTracker
from sklearn.ensemble import RandomForestClassifier as ThisModel

#%%
#
# Set up model for training
#
this_model = ModelTrainer(
    ModelClass=ThisModel,  #Model algorithm
    model_params=dict(n_estimators=200, max_depth=5,
                      n_jobs=-1),  #hyper-parameters
    model_id='L1RF1',  # Model Identifier
    feature_set='L1FS01'  # feature set to use
)

model_tracker = ModelPerformanceTracker(model_trainer=this_model)
#%%
#
# clear out old results
#
this_model.cleanPriorResults()

#%%
#
# train model on all the data
#
this_model.trainModel()

#%%

Example #3

# -*- coding: utf-8 -*-
#%%
from framework.model_stacking import ModelTrainer, ModelPerformanceTracker
from sklearn.linear_model import LogisticRegression as ThisModel

#%%
#
# Set up model for training
#
this_model = ModelTrainer(
    ModelClass=ThisModel,  #Model algorithm
    model_params=dict(penalty='l1', C=0.1, tol=1e-5,
                      random_state=13),  #hyper-parameters
    model_id='L0LOG1',  # Model Identifier
    feature_set='KFS04'  # feature set to use
)

model_tracker = ModelPerformanceTracker(model_trainer=this_model)
#%%
#
# clear out old results
#
this_model.cleanPriorResults()

#%%
#
# train model on all the data
#
this_model.trainModel()

#%%

Example #4

# -*- coding: utf-8 -*-
#%%
from framework.model_stacking import ModelTrainer, ModelPerformanceTracker
from xgboost import XGBClassifier as ThisModel

#%%
#
# Set up model for training
#
this_model = ModelTrainer(
        ModelClass=ThisModel,  #Model algorithm
        model_params=dict(n_estimators=100,n_jobs=6), #hyper-parameters
        model_id='L0XGB1',   # Model Identifier
        feature_set='KFSBSLN'  # feature set to use
        )

model_tracker = ModelPerformanceTracker(model_trainer=this_model)
#%%
#
# clear out old results
#
this_model.cleanPriorResults()

#%%
#
# train model on all the data
#
this_model.trainModel()

#%%
# create Test predictions