gangchen

svmrfeFeatureRanking = function(x,y){ 
	n = ncol(x)
	survivingFeaturesIndexes = seq(1:n) 
	featureRankedList = vector(length=n) 
	rankedFeatureIndex = n

	while(length(survivingFeaturesIndexes)>0){ 

		#train the support vector machine 
		svmModel = svm(x[, survivingFeaturesIndexes], y, cost = 10, cachesize=500,scale=F, type="C-classification", kernel="linear" )	

gangchen

# Examples for R training
# Author: Gang Chen <chengang@genomics.cn>
# Nov 2012

# Lesson 2
# vector
a <- c(1, 2, 5, 3, 6, -2, 4)
b <- c("one", "two", "three")
c <- c(TRUE, TRUE, TRUE, FALSE, TRUE, FALSE)

gangchen

 All
 Abnormality of body height
 Multicystic kidney dysplasia
 Mode of inheritance
 Autosomal dominant inheritance
 Autosomal recessive inheritance
 Abnormality of female internal genitalia
 Functional abnormality of the bladder
 Recurrent urinary tract infections
 Neurogenic bladder

gangchen

import tensorflow as tf
import numpy as np

data = np.array([
  [-2.0, -1],  # Alice
  [25, 6],   # Bob
  [17, 4],   # Charlie
  [-15, -6], # Diana
])
all_y_trues = np.array([

gangchen

# 其实用可用来问卷星上爬各种公开的带答案的问卷
# 现在这个网址是广东省2022年PCR实验员资格考试的练习题问卷

from requests_html import HTMLSession
 
wenjuanxing_URL = "https://ks.wjx.top/vm/QqNTNBr.aspx"
 
def parse_post_data(resp):

    print(resp.html.links)