Skip to main content

MALSS: MAchine Learning Support System

Project description

malss is a python module to facilitate machine learning tasks. This module is written to be compatible with the scikit-learn algorithms and the other scikit-learn-compatible algorithms.

https://travis-ci.org/canard0328/malss.svg?branch=master

Requirements

These are external packages which you will need to install before installing malss.

  • python (>= 2.7 or >= 3.4)
  • numpy (>= 1.10.2)
  • scipy (>= 0.16.1)
  • scikit-learn (>= 0.18)
  • matplotlib (>= 1.5.1)
  • pandas (>= 0.14.1)
  • jinja2 (>= 2.8)

I highly recommend Anaconda. Anaconda conveniently installs packages listed above.

Installation

If you already have a working installation of numpy and scipy:

pip install malss

If you have not installed numpy or scipy yet, you can also install these using pip.

Example

Classification:

from malss import MALSS
from sklearn.datasets import load_iris
iris = load_iris()
clf = MALSS('classification')
clf.fit(iris.data, iris.target, 'classification_result')
clf.generate_module_sample('classification_module_sample.py')

Regression:

from malss import MALSS
from sklearn.datasets import load_boston
boston = load_boston()
clf = MALSS('regression')
clf.fit(boston.data, boston.target, 'regression_result')
clf.generate_module_sample('regression_module_sample.py')

Change algorithm:

from malss import MALSS
from sklearn.datasets import load_iris
from sklearn.ensemble import RandomForestClassifier as RF
iris = load_iris()
clf = MALSS('classification')
clf.fit(iris.data, iris.target, algorithm_selection_only=True)
algorithms = clf.get_algorithms()
# check algorithms here
clf.remove_algorithm(0)
clf.add_algorithm(RF(n_jobs=3),
                  [{'n_estimators': [10, 30, 50],
                    'max_depth': [3, 5, None],
                    'max_features': [0.3, 0.6, 'auto']}],
                  'Random Forest')
clf.fit(iris.data, iris.target, 'classification_result')
clf.generate_module_sample('classification_module_sample.py')

API

View the documentation here.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
malss-1.1.3-py2.py3-none-any.whl (21.1 kB) Copy SHA256 hash SHA256 Wheel py2.py3 Jan 26, 2018

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page