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<?php | |
$hosts = array('slave_host01', 'slave_host02', 'slave_host03'); | |
foreach ($hosts as $host) { | |
exec("ssh $host /usr/java/default/bin/jps | /bin/grep 'DataNode\|TaskTracker' | /bin/sed 's/\([0-9]\) .*/\1/'", $pids); | |
foreach ($pids as $pid) { | |
exec("ssh $host kill $pid); | |
} | |
} |
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# import data | |
data <- read.delim(testadata.txt") | |
# execute regression and plot confidence/predict interval | |
predict_continue <- function(target_method, target_cpa, interval) { | |
d <- subset(data, method==target) | |
# regression using log() transformation | |
d.lm <- lm(continue~log(month)+cpa, data=d) | |
summary(d.lm) | |
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source("http://aoki2.si.gunma-u.ac.jp/R/src/pairwise.prop2.test.R", encoding="euc-jp") | |
x <- matrix(c(18, 82, 40, 76, 32, 52), ncol=2, byrow=T) | |
x | |
chisq.test(x) | |
fisher.test(x) | |
pairwise.prop2.test(x, p.adjust.method="holm", test.function=chisq.test) |
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x <- matrix(c(1, 1, 1, 1, 1, 1, 3, 7, 1, 5, 4, 2), 6, 2) #素性ベクトル | |
l <- c(-1, 1, -1, 1, 1, -1) #ラベル | |
w <- c(0, 0) #重みベクトル | |
r <- 0.5 #学習係数 | |
#重みベクトルの更新メソッド | |
update <- function(x, l, w) { | |
if (sign(x %*% w) == sign(l)) { | |
return(w) | |
} |
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#パラメタ | |
x <- matrix(c(1, 1, 1, 1, 1, 1, 3, 7, 1, 5, 4, 2), 6, 2) #素性ベクトル | |
l <- c(-1, 1, -1, 1, 1, -1) #ラベル | |
w <- c(0, 0) #重みベクトル | |
r <- 0.5 #学習係数 | |
#重みベクトルの更新メソッド | |
update <- function(x, l, w) { | |
if (sign(x %*% w) == sign(l)) { | |
return(w) |
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team team_no number era game win lose winning_rate WHIP DIPS | |
giants 1 19 3.12 27 13 6 0.684 1.15 2.81 | |
giants 1 26 3.31 25 13 6 0.684 1.27 3.65 | |
giants 1 15 3.13 34 5 10 0.333 1.14 3.64 | |
giants 1 18 3.35 24 11 6 0.647 1.12 3.87 | |
tigers 2 54 2.89 30 12 8 0.6 1.17 3.03 | |
tigers 2 14 2.69 25 11 7 0.611 1.08 3.67 | |
tigers 2 55 2.74 26 8 12 0.4 1.29 3.46 | |
curp 3 18 2.1 26 15 7 0.682 0.96 2.98 | |
curp 3 42 3.23 28 11 9 0.55 1.13 3.97 |
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team teme_no OPS DER DEF | |
giants 1 0.728 0.706 0.988 | |
tigers 2 0.686 0.704 0.989 | |
curp 3 0.688 0.697 0.981 | |
dragons 4 0.676 0.688 0.986 | |
baysters 5 0.717 0.675 0.983 | |
swallows 6 0.705 0.683 0.988 | |
goldeneagles 7 0.719 0.681 0.986 | |
lions 0.696 8 0.693 0.988 | |
marines 9 0.708 0.695 0.986 |
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#!/usr/bin/env python | |
#-*-coding:utf-8-*- | |
import argparse | |
# args | |
parser = argparse.ArgumentParser() | |
parser.add_argument('text') | |
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library(randomForest) | |
# load data | |
data = read.delim("data/sample.tsv", sep="\t") | |
# create data for k-fold cross validation | |
cv = function(d, k) { | |
n = sample(nrow(d), nrow(d)) | |
d.randomized = data[n,] # randomize data | |
n.residual = k-nrow(d)%%k |
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