Solve weak classifier

Add kernel liblinear with LinearSVC classifier
Set ovo strategy as default

Makefile

@@ -1,6 +1,6 @@
 SHELL := /bin/bash
 .DEFAULT_GOAL := help
-.PHONY: coverage deps help lint push test doc build
+.PHONY: coverage deps help lint push test
 
 coverage:  ## Run tests with coverage
 	coverage erase
@@ -24,13 +24,6 @@ test:  ## Run tests
 doc:  ## Update documentation
 	make -C docs --makefile=Makefile html
 
-build:  ## Build package
-	rm -fr dist/*
-	python setup.py sdist bdist_wheel
-
-doc-clean:  ## Update documentation
-	make -C docs --makefile=Makefile clean
-
 help: ## Show help message
 	@IFS=$$'\n' ; \
 	help_lines=(`fgrep -h "##" $(MAKEFILE_LIST) | fgrep -v fgrep | sed -e 's/\\$$//' | sed -e 's/##/:/'`); \
@@ -46,4 +39,4 @@ help: ## Show help message
 		printf "%-20s %s" $$help_command ; \
 		printf '\033[0m'; \
 		printf "%s\n" $$help_info; \
-	done
+	done

README.md

@@ -1,9 +1,8 @@
 ![CI](https://github.com/Doctorado-ML/STree/workflows/CI/badge.svg)
 [![codecov](https://codecov.io/gh/doctorado-ml/stree/branch/master/graph/badge.svg)](https://codecov.io/gh/doctorado-ml/stree)
 [![Codacy Badge](https://app.codacy.com/project/badge/Grade/35fa3dfd53a24a339344b33d9f9f2f3d)](https://www.codacy.com/gh/Doctorado-ML/STree?utm_source=github.com&utm_medium=referral&utm_content=Doctorado-ML/STree&utm_campaign=Badge_Grade)
-[![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/Doctorado-ML/STree.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/Doctorado-ML/STree/context:python)
 
-# STree
+# Stree
 
 Oblique Tree classifier based on SVM nodes. The nodes are built and splitted with sklearn SVC models. Stree is a sklearn estimator and can be integrated in pipelines, grid searches, etc.
 

docs/requirements.txt

@@ -1,4 +1,3 @@
 sphinx
 sphinx-rtd-theme
 myst-parser
-git+https://github.com/doctorado-ml/stree

docs/source/conf.py

@@ -12,7 +12,6 @@
 #
 import os
 import sys
-import stree
 
 sys.path.insert(0, os.path.abspath("../../stree/"))
 
@@ -24,8 +23,7 @@ copyright = "2020 - 2021, Ricardo Montañana Gómez"
 author = "Ricardo Montañana Gómez"
 
 # The full version, including alpha/beta/rc tags
-version = stree.__version__
-release = version
+release = "1.0"
 
 
 # -- General configuration ---------------------------------------------------

docs/source/stree.md

@@ -1,9 +1,8 @@
-# STree
+# Stree
 
 [![Codeship Status for Doctorado-ML/STree](https://app.codeship.com/projects/8b2bd350-8a1b-0138-5f2c-3ad36f3eb318/status?branch=master)](https://app.codeship.com/projects/399170)
 [![codecov](https://codecov.io/gh/doctorado-ml/stree/branch/master/graph/badge.svg)](https://codecov.io/gh/doctorado-ml/stree)
 [![Codacy Badge](https://app.codacy.com/project/badge/Grade/35fa3dfd53a24a339344b33d9f9f2f3d)](https://www.codacy.com/gh/Doctorado-ML/STree?utm_source=github.com&utm_medium=referral&utm_content=Doctorado-ML/STree&utm_campaign=Badge_Grade)
-[![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/Doctorado-ML/STree.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/Doctorado-ML/STree/context:python)
 
 Oblique Tree classifier based on SVM nodes. The nodes are built and splitted with sklearn SVC models. Stree is a sklearn estimator and can be integrated in pipelines, grid searches, etc.
 

setup.py

@@ -1,4 +1,5 @@
 import setuptools
+import stree
 
 
 def readme():
@@ -6,23 +7,11 @@ def readme():
         return f.read()
 
 
-def get_data(field):
-    item = ""
-    with open("stree/__init__.py") as f:
-        for line in f.readlines():
-            if line.startswith(f"__{field}__"):
-                delim = '"' if '"' in line else "'"
-                item = line.split(delim)[1]
-                break
-        else:
-            raise RuntimeError(f"Unable to find {field} string.")
-    return item
-
-
+VERSION = stree.__version__
 setuptools.setup(
     name="STree",
-    version=get_data("version"),
-    license=get_data("license"),
+    version=stree.__version__,
+    license=stree.__license__,
     description="Oblique decision tree with svm nodes",
     long_description=readme(),
     long_description_content_type="text/markdown",
@@ -32,19 +21,19 @@ setuptools.setup(
         "Code": "https://github.com/Doctorado-ML/STree",
         "Documentation": "https://stree.readthedocs.io/en/latest/index.html",
     },
-    author=get_data("author"),
-    author_email=get_data("author_email"),
+    author=stree.__author__,
+    author_email=stree.__author_email__,
     keywords="scikit-learn oblique-classifier oblique-decision-tree decision-\
     tree svm svc",
     classifiers=[
         "Development Status :: 5 - Production/Stable",
-        "License :: OSI Approved :: " + get_data("license"),
+        "License :: OSI Approved :: " + stree.__license__,
         "Programming Language :: Python :: 3.8",
         "Natural Language :: English",
         "Topic :: Scientific/Engineering :: Artificial Intelligence",
         "Intended Audience :: Science/Research",
     ],
-    install_requires=["scikit-learn", "numpy"],
+    install_requires=["scikit-learn", "numpy", "ipympl"],
     test_suite="stree.tests",
     zip_safe=False,
 )

stree/.readthedocs.yaml

@@ -1,10 +0,0 @@
-version: 2
-
-sphinx:
-  configuration: docs/source/conf.py
-
-python:
-  version: 3.8
-  install:
-    - requirements: requirements.txt
-    - requirements: docs/requirements.txt