baselines

a python package used for benchmarking algorithms over various datasets

Installation

pip install base2lines

Introduction

Data class :

show_datasets:

show available datasets

load_dataset :

load specific dataset (pass name as argument)

Classification class :

classification method:

parameters:

dataset in csv format or pandas dataframe with classification column at last

result:

returns benchmark for dataset with various algorithms and its f1_score

Regression Class:

regressor method:

parameters:

dataset (pandas dataframe)

resultantColumn (name of column which has the value to be predicted)

Pipeline Class:

init method:

parameters:

dataset (pandas dataframe)

show_graph method:

parameters:

pipeline_show (sklearn Pipeline object which will be inturn turned to graph)

How to use

Data Class

from baseline.Data import Data
data = Data()
dataset_names = data.show_dataset()
#name should be only from dataset_names 
dataset = data.load_dataset('name') 

Classification Class

from baseline.classification import Classification
classifier = Classification()
# dataset's last column should be the column to be classified
results = classifier.classification(dataset)
print(results)

Regression Class

from baseline.regression import Regression
regressors = Regression()
# also pass the resultant column
results = regressors.regressor(dataset , resultantColumn)
print(results)

Pipeline Class

from baseline.pipeline import Pipeline
graph = Pipeline(dataset)
#pipeline should only have sklearn components
graph.show_graph(pipelineToBeShown)