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alyato / xgboost_python_install.md
Created November 29, 2018 07:23 — forked from pratos/xgboost_python_install.md
Install xgboost for Python in Ubuntu

Clone the recursive repo for xgboost

git clone --recursive https://github.com/dmlc/xgboost
cd xgboost
make -j4

cd in the folder: xgboost/python-package

@alyato
alyato / gist:44541b955e788fd91e96ff65388d5ed5
Created April 27, 2017 08:23 — forked from ngn999/gist:3168642
Emacs 常用Mode

学会基本操作后,值得细究的Mode:

  • CC Mode, 写C/C++代码, 管理缩进,高亮
  • Cperl Mode, 写Perl代码, 比Perl Mode更强.
  • Python Mode
  • eshell, M-x shell RET
  • Diff Mode / Ediff Mode, 看diff, 做merge操作.
  • VC, 与版本管理系统相接合,支持CVS, SVN, Git etc.
  • Hippie Expand, M-/
  • Dired Mode, 文件, 目录管理. copy, mv, rename. create
@alyato
alyato / 中国历代年表
Created April 21, 2017 03:10 — forked from xuchunyang/中国历代年表
旧石器时代
中石器时期
黄河文明
长江文明
新石器时期
@alyato
alyato / sda.py
Created August 5, 2016 13:42 — forked from pyben/sda.py
import numpy as np
from keras.datasets import imdb
from keras.preprocessing.sequence import pad_sequences
from keras.models import Sequential
from keras.layers import containers
from keras.layers.noise import GaussianNoise
from keras.layers.core import Dense, AutoEncoder
from keras.utils import np_utils
from sklearn.metrics import (precision_score, recall_score,
@alyato
alyato / TEST_SVM_ON_VIPER.md
Created May 24, 2016 00:26 — forked from alanse7en/TEST_SVM_ON_VIPER.md
#实验结果

Training phase

20000 training instances The number of support vectors is around 15000, which means that most of the training data are near the separating hyper-plane. The training accuracy is around 80%

Test on full data

  • Accuracy = 52.3734% (662/1264) (classification)
  • Accuracy = 62.5791% (791/1264) (classification)
  • Accuracy = 61.0759% (772/1264) (classification)
  • Accuracy = 60.9968% (771/1264) (classification)