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pkg/ | |
src/ | |
understand-bin-*.pkg.* | |
Understand-*.tgz | |
.SRCINFO |
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print('start') | |
import pandas as pd | |
from sklearn.linear_model import LogisticRegression #导入线性回归库 | |
from sklearn.feature_extraction.text import CountVectorizer #导入特征提取库 | |
#读取文件,并且删除无关东西 | |
df_train = pd.read_csv('/Users/apple/Documents/ST/python/competition/DataCastel/text_intelligence/new_data/train_set.csv') | |
df_test = pd.read_csv('/Users/apple/Documents/ST/python/competition/DataCastel/text_intelligence/new_data/test_set.csv') | |
df_train.drop(columns =['article', 'id'], inplace = True ) #问题1: 为什么要删除这两个列,id列没有意义,不需要用article,直接删除 | |
df_test.drop(columns =['article'], inplace = True ) |
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print('start') | |
import pandas as pd | |
from sklearn.linear_model import LogisticRegression #导入线性回归库 | |
from sklearn.feature_extraction.text import CountVectorizer #导入特征提取库 | |
#读取文件,并且删除无关东西 | |
df_train = pd.read_csv('/Users/apple/Documents/ST/python/competition/DataCastel/text_intelligence/new_data/train_set.csv') | |
df_test = pd.read_csv('/Users/apple/Documents/ST/python/competition/DataCastel/text_intelligence/new_data/test_set.csv') | |
df_train.drop(columns =['article', 'id'], inplace = True ) #问题1: 为什么要删除这两个列,id列没有意义,不需要用article,直接删除 | |
df_test.drop(columns =['article'], inplace = True ) |
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import numpy as np | |
from sklearn.datasets import make_classification | |
from slmethod.perceptron import Perceptron | |
separable = False | |
while not separable: | |
samples = make_classification(n_samples=100, | |
n_features=2, | |
n_redundant=0, | |
n_informative=1, |
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#!/usr/bin/env python3 | |
# -*- coding: utf-8 -*- | |
l = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100] | |
pre = 1 | |
post = 1 | |
diff = 2 | |
index = -1 |
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#!/usr/bin/env python3 | |
# -*- coding: utf-8 -*- | |
import requests | |
import json | |
import os | |
from pprint import pprint | |
upload_url = 'https://upload.qiniup.com/' |
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#!/usr/bin/env python3 | |
# -*- coding: utf-8 -*- | |
import os | |
import time | |
from googletrans import Translator | |
translator = Translator() | |
def translate(src): |
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#!/usr/bin/env python3 | |
# -*- coding: utf-8 -*- | |
import json | |
import collections | |
def readMd(mdfile): | |
with open(mdfile) as f: | |
lines = f.readlines() | |
lines = list(map(lambda l: l.rstrip(), lines)) |
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#!/bin/bash | |
# Copyright 2017 Théo Chamley | |
# 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, distribute, sublicense, and/or sell copies of the Software, and to permit persons | |
# to whom the Software is furnished to do so, subject to the following conditions: | |
# | |
# The above copyright notice and this permission notice shall be included in all copies or |
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// MARK: Using NSURLSession | |
// Get first todo item | |
let todoEndpoint: String = "http://jsonplaceholder.typicode.com/todos/1" | |
guard let url = NSURL(string: todoEndpoint) else { | |
print("Error: cannot create URL") | |
return | |
} | |
let urlRequest = NSURLRequest(URL: url) |