Exemplos de ExperimentController.run_experiment em Python

Exemplo n.º 1

def run_tc3_0():
    global dataset, feature_extraction_method, classifiers, experiment_controller
    dataset = Dataset.arxiv_metadata
    feature_extraction_method = FeatureExtractionMethod.BOW
    classifiers = [ClassificationMethod.Gradient_Boosting_Machines]

    experiment_controller = ExperimentController('tc#3.0', '3')
    experiment_controller.set_variables(dataset,
                                        feature_extraction_method,
                                        classifiers,
                                        should_load_embedding_model=False)
    experiment_controller.run_experiment()

Exemplo n.º 2

Arquivo: tc#0.py Projeto: Anamitr/master-thesis

def run_tc0_0():
    global dataset, feature_extraction_method, classifiers, experiment_controller
    dataset = Dataset.ds20newsgroups
    feature_extraction_method = FeatureExtractionMethod.BOW
    classifiers = [
        ClassificationMethod.Naive_Bayes_Classifier,
        # ClassificationMethod.Logistic_Regression,
        ClassificationMethod.Support_Vector_Machines,
        ClassificationMethod.SVM_with_SGD
    ]

    experiment_controller = ExperimentController('tc#0.0', '1')
    experiment_controller.set_variables(dataset, feature_extraction_method,
                                        classifiers)
    experiment_controller.run_experiment()

Exemplo n.º 3

def run_tc3_4():
    global dataset, feature_extraction_method, classifiers, experiment_controller
    dataset = Dataset.arxiv_metadata
    feature_extraction_method = FeatureExtractionMethod.FASTTEXT
    classifiers = [
        ClassificationMethod.Logistic_Regression,
        ClassificationMethod.Support_Vector_Machines,
        ClassificationMethod.SVM_with_SGD
    ]

    experiment_controller = ExperimentController('tc#3.4', '2')
    experiment_controller.set_variables(dataset,
                                        feature_extraction_method,
                                        classifiers,
                                        should_load_embedding_model=False)
    experiment_controller.run_experiment()

Exemplo n.º 4

Arquivo: tc#0.py Projeto: Anamitr/master-thesis

def run_tc0_2():
    global dataset, feature_extraction_method, classifiers, experiment_controller
    dataset = Dataset.ds20newsgroups
    feature_extraction_method = FeatureExtractionMethod.WORD2VEC
    classifiers = [
        ClassificationMethod.Naive_Bayes_Classifier,
        ClassificationMethod.Logistic_Regression,
        ClassificationMethod.Support_Vector_Machines,
        ClassificationMethod.SVM_with_SGD
    ]

    experiment_controller = ExperimentController('tc#0.2', '1')
    experiment_controller.set_variables(dataset,
                                        feature_extraction_method,
                                        classifiers,
                                        should_load_embedding_model=True)
    experiment_controller.run_experiment()

Exemplo n.º 5

def run_tc3_1():
    global dataset, feature_extraction_method, classifiers, experiment_controller
    dataset = Dataset.arxiv_metadata
    feature_extraction_method = FeatureExtractionMethod.TF_IDF
    classifiers = [
        ClassificationMethod.Naive_Bayes_Classifier,
        ClassificationMethod.Logistic_Regression,
        ClassificationMethod.Support_Vector_Machines,
        ClassificationMethod.SVM_with_SGD,
        ClassificationMethod.Gradient_Boosting_Machines
    ]

    experiment_controller = ExperimentController('tc#3.1', '2')
    experiment_controller.set_variables(dataset,
                                        feature_extraction_method,
                                        classifiers,
                                        should_load_embedding_model=False)
    experiment_controller.run_experiment()

Exemplo n.º 6

Arquivo: tc#2.4.py Projeto: Anamitr/master-thesis

import warnings

# %matplotlib inline
from topic_classification.ExperimentController import ExperimentController
from topic_classification.constants import *

warnings.filterwarnings('ignore')
# Script for different kind of experiments

dataset = Dataset.bbc_news_summary
feature_extraction_method = FeatureExtractionMethod.FASTTEXT
classifiers = [
    ClassificationMethod.Logistic_Regression,
    ClassificationMethod.Support_Vector_Machines,
    ClassificationMethod.SVM_with_SGD
]

experiment_controller = ExperimentController('tc#2.4', '1')
experiment_controller.run_experiment(dataset,
                                     feature_extraction_method,
                                     classifiers,
                                     should_load_embedding_model=True)