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# Back-Propagation Neural Networks | |
# | |
# Written in Python. See http://www.python.org/ | |
# Modified by JSun to solve the problem here: http://www.weibo.com/1497035431/ynPEvC78V | |
# Neil Schemenauer <nas@arctrix.com> | |
import math | |
import random | |
import string |
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#!/usr/bin/env python | |
# Problem: http://www.weibo.com/2090476735/ynJtWvN1K | |
# junyi sun (weibo.com/treapdb) | |
from numpy import * | |
def Q(L): | |
H = [0]*11 | |
H[0] = 1 #bias item | |
for x in L: | |
H[x+1]+=1 |
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# Back-Propagation Neural Networks | |
# another way: solve it as a Regression Problem | |
# Written in Python. See http://www.python.org/ | |
# Modified by JSun to solve the problem here: http://www.weibo.com/1497035431/ynPEvC78V | |
# Neil Schemenauer <nas@arctrix.com> | |
import math | |
import random | |
import string |
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var http=require('http') | |
url =require("url") | |
var cluster = require('cluster'); | |
if (cluster.isMaster) { | |
// Fork workers. | |
for (var i = 0; i < 20; i++) { | |
cluster.fork(); | |
} |
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import random | |
import time | |
size=100000000 | |
t1 = time.time() | |
f=open('x.db','wb') | |
f.write('x'*size) | |
f.close() | |
print 'write:', time.time()-t1 | |
f=open('x.db','rb') | |
t2=time.time() |
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var QBuffer = exports.QBuffer= function(){ | |
this.list = [] | |
this.length = 0 | |
} | |
QBuffer.prototype.append=function(chunk){ | |
this.list.push(chunk) | |
this.length += chunk.length | |
} |
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package main | |
import ( | |
"net" | |
"log" | |
"fmt" | |
"bufio" | |
"strings" | |
"strconv" | |
"io" |
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package main | |
import ( | |
"net/http" | |
"net/url" | |
"log" | |
"io/ioutil" | |
"regexp" | |
"fmt" | |
//"net/http/httputil" |
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package main | |
import ( | |
"net/http" | |
"net/url" | |
"log" | |
"io/ioutil" | |
"regexp" | |
"fmt" | |
//"net/http/httputil" |
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#!/usr/bin/python | |
import numpy.random as random | |
from bisect import bisect_left, bisect_right | |
class SlaveNode: | |
def __init__ (self, data): | |
self.data = sorted(data) | |
def get_range (self): |
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