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| #include<iostream> | |
| using namespace std; | |
| const int DATAGRAM_LENGTH = 64; | |
| const int BIT_LENGTH = 8; | |
| void text_to_bin(string block, bool output[DATAGRAM_LENGTH]) { | |
| int current = 0; | |
| for (int i = 0;i < block.length();i++) { |
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| #include<iostream> | |
| using namespace std; | |
| void printArray(bool *list, int size) { | |
| for(int i = 0; i < size; i++){ | |
| cout << list[i]; | |
| } |
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| #include <stdio.h> | |
| #include <string.h> | |
| int main() { | |
| char c1 = 0; | |
| char c2 = '\0'; | |
| char c3 = '0'; | |
| if (c2 == c1) { | |
| puts("Wut, wut!"); | |
| } else if (c1 == c3) { |
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| library(foreign) | |
| library(caret) | |
| library(cluster) | |
| library(mclust) | |
| library(ggbiplot) | |
| # http://rpubs.com/sinhrks/plot_pca | |
| library(ggfortify) | |
| library(fastICA) | |
| library(nnet) | |
| library(doMC) |
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| --- | |
| # Installs h2o and supporting files | |
| - name: Create User | |
| user: name="{{ h2o_user }}" | |
| - name: Download | |
| unarchive: src="{{ h2o_url }}" | |
| dest=/tmp/ | |
| copy=no | |
| creates="/tmp/{{ h2o_name }}" |
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| bool temp[64] = {0}; | |
| cout << "message: " << message.substr(0,8) << endl; | |
| for(int i=0; i<8; i++) { | |
| bitset<8> tempbyte(message[i]); | |
| cout << "digit: " << i+1 << " - " ; | |
| for(int j=0;j<8;j++) { | |
| int count = (i*8)+j; | |
| if(tempbyte[7-j]) { |
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| #include<iostream> | |
| #include<bitset> | |
| #include<vector> | |
| class BoolVec { | |
| public: | |
| const std::string ascii; | |
| BoolVec(const std::string st) : | |
| ascii(st), | |
| result(st.size() * 8, 0), |
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| unbind-key C-b | |
| set-option -g prefix C-s | |
| bind-key C-s last-window | |
| bind s send-prefix | |
| # large history | |
| set-option -g history-limit 100000 | |
| # enable mouse mode |
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| library(ggplot2) | |
| library(data.table) | |
| source("multiplot.R") | |
| RESULTS="results" | |
| GRAPHS="graphs" | |
| nnet.graph <- function(dat, method="point", metric="error") { | |
| # melting operation for the error & time columns simultaneously | |
| d1 <- melt(setDT(dat), measure.vars = patterns(".error",".time"), value.name = c("error","time")) |
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| algorithm | iterations | time | optim | |
|---|---|---|---|---|
| MIMIC | 1 | 0.03 | 56 | |
| MIMIC | 10001 | 29.6 | 78 | |
| MIMIC | 1001 | 6.56 | 75 | |
| MIMIC | 101 | 0.88 | 70 | |
| MIMIC | 1021 | 6.7 | 75 | |
| MIMIC | 1041 | 6.79 | 75 | |
| MIMIC | 1061 | 6.73 | 75 | |
| MIMIC | 1081 | 6.95 | 73 | |
| MIMIC | 1101 | 6.62 | 73 |