repo_name stringlengths 9 55 | path stringlengths 7 120 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 1.02k 169k | license stringclasses 12
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joshbohde/scikit-learn | examples/plot_permutation_test_for_classification.py | 2 | 2049 | """
=================================================================
Test with permutations the significance of a classification score
=================================================================
In order to test if a classification score is significative a technique
in repeating the classification procedure aft... | bsd-3-clause |
CG-F16-24-Rutgers/steersuite-rutgers | steerstats/tools/plotting/plotMultiObjectiveData.py | 8 | 1340 |
import csv
import matplotlib.pyplot as plt
import sys
import numpy as np
# filename = '../../data/optimization/sf/multiObjective/SteerStatsOpt2.csv'
filename = sys.argv[1]
xs = []
ys = []
if len(sys.argv) == 2:
csvfile = open(filename, 'r')
spamreader = csv.reader(csvfile, delimiter=',')
xs = []
ys =... | gpl-3.0 |
maxlikely/scikit-learn | sklearn/pipeline.py | 1 | 13051 | """
The :mod:`sklearn.pipeline` module implements utilites to build a composite
estimator, as a chain of transforms and estimators.
"""
# Author: Edouard Duchesnay
# Gael Varoquaux
# Virgile Fritsch
# Alexandre Gramfort
# Licence: BSD
import numpy as np
from scipy import sparse
from .base impo... | bsd-3-clause |
martinggww/lucasenlights | MachineLearning/python_tutorial/KNearestNeighborhood.py | 1 | 1274 | '''
Classification algorithm
Create a model that seperate a dataset
proximity probability nearest neighbors
What the hack is K?
if K=2, find the closet 2 points
We want K = odd numbers, K=3, 5, 7...
'''
'''
- - +, 66.7% confidence, confidence, accuracy
Euclid distance, euclid distance middle point
Dataset and the rela... | cc0-1.0 |
treycausey/scikit-learn | sklearn/feature_selection/__init__.py | 244 | 1088 | """
The :mod:`sklearn.feature_selection` module implements feature selection
algorithms. It currently includes univariate filter selection methods and the
recursive feature elimination algorithm.
"""
from .univariate_selection import chi2
from .univariate_selection import f_classif
from .univariate_selection import f_... | bsd-3-clause |
chenyyx/scikit-learn-doc-zh | examples/zh/cluster/plot_dict_face_patches.py | 9 | 2747 | """
Online learning of a dictionary of parts of faces
==================================================
This example uses a large dataset of faces to learn a set of 20 x 20
images patches that constitute faces.
From the programming standpoint, it is interesting because it shows how
to use the online API of the sciki... | gpl-3.0 |
jrcapriles/gameSimulator | gameSimulator.py | 1 | 6837 | # -*- coding: utf-8 -*-
"""
Created on Thu Sep 18 19:27:57 2014
@author: joser
"""
import pygame, ode, random, Buttons
from math import atan2, acos, asin, sin, cos
import matplotlib.pyplot as plt
from pygame.locals import *
from numpy import *
from Point import *
from Buttons import *
class gameSimulator( object ... | mit |
stevenzhang18/Indeed-Flask | lib/pandas/tests/test_expressions.py | 9 | 16557 | # -*- coding: utf-8 -*-
from __future__ import print_function
# pylint: disable-msg=W0612,E1101
import nose
import re
from numpy.random import randn
import operator
import numpy as np
from pandas.core.api import DataFrame, Panel
from pandas.computation import expressions as expr
from pandas import compat
from pand... | apache-2.0 |
drusk/pml | pml/unsupervised/clustering.py | 1 | 11112 | # Copyright (C) 2012 David Rusk
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to
# deal in the Software without restriction, including without limitation the
# rights to use, copy, modify, merge, publish, distr... | mit |
r39132/airflow | tests/contrib/operators/test_hive_to_dynamodb_operator.py | 7 | 5053 | # -*- coding: utf-8 -*-
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
#... | apache-2.0 |
jiangzhonglian/MachineLearning | src/py2.x/ml/6.SVM/svm-complete_Non-Kernel.py | 1 | 13440 | #!/usr/bin/python
# coding:utf8
"""
Created on Nov 4, 2010
Update on 2017-05-18
Chapter 5 source file for Machine Learing in Action
Author: Peter/geekidentity/片刻
GitHub: https://github.com/apachecn/AiLearning
"""
from __future__ import print_function
from numpy import *
import matplotlib.pyplot as plt
class optStruc... | gpl-3.0 |
Titan-C/sympy | sympy/physics/quantum/circuitplot.py | 6 | 12937 | """Matplotlib based plotting of quantum circuits.
Todo:
* Optimize printing of large circuits.
* Get this to work with single gates.
* Do a better job checking the form of circuits to make sure it is a Mul of
Gates.
* Get multi-target gates plotting.
* Get initial and final states to plot.
* Get measurements to plo... | bsd-3-clause |
LiaoPan/scikit-learn | examples/svm/plot_iris.py | 225 | 3252 | """
==================================================
Plot different SVM classifiers in the iris dataset
==================================================
Comparison of different linear SVM classifiers on a 2D projection of the iris
dataset. We only consider the first 2 features of this dataset:
- Sepal length
- Se... | bsd-3-clause |
joernhees/scikit-learn | sklearn/ensemble/weight_boosting.py | 29 | 41090 | """Weight Boosting
This module contains weight boosting estimators for both classification and
regression.
The module structure is the following:
- The ``BaseWeightBoosting`` base class implements a common ``fit`` method
for all the estimators in the module. Regression and classification
only differ from each ot... | bsd-3-clause |
NolanBecker/aima-python | grading/neuralNet-submissions.py | 4 | 2217 | import importlib
import traceback
from grading.util import roster, print_table
# from logic import FolKB
# from utils import expr
import os
from sklearn.neural_network import MLPClassifier
mlpc = MLPClassifier()
def indent(howMuch = 1):
space = ' '
for i in range(1, howMuch):
space += ' '
return s... | mit |
guillemborrell/gtable | tests/test_table_creation.py | 1 | 4044 | from gtable import Table
import numpy as np
import pandas as pd
def test_empty_table():
t = Table()
assert t.data == []
def test_simple_table():
t = Table({'a': [1, 2, 3], 'b': np.array([4, 5, 6])})
assert t.to_dict()['a'][2] == 3
assert np.all(t.index == np.ones((2, 3), dtype=np.uint8))
... | bsd-3-clause |
sysid/nbs | ml_old/Prognose/Evaluator.py | 1 | 3134 | from twBase import * # NOQA
from pandas import DataFrame
from pandas import read_csv
from pandas import datetime
from sklearn.preprocessing import MinMaxScaler
# date-time parsing function for loading the dataset
def parser(x):
return datetime.strptime('190'+x, '%Y-%m')
def get_time():
return time.strftime(... | mit |
jjo31/ATHAM-Fluidity | tests/gls-Kato_Phillips-mixed_layer_depth/mixed_layer_depth_all.py | 4 | 4600 | #!/usr/bin/env python
from numpy import arange,concatenate,array,argsort
import os
import sys
import vtktools
import math
from pylab import *
from matplotlib.ticker import MaxNLocator
import re
from scipy.interpolate import UnivariateSpline
import glob
#### taken from http://www.codinghorror.com/blog/archives/001018... | lgpl-2.1 |
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