Python T-sne降维_coolsunxu的博客

import csv
import numpy as np
from sklearn.preprocessing import StandardScaler
from sklearn import manifold
import matplotlib.pyplot as plt
import random

import math


temp = []


with open('qsar_fish_toxicity.csv') as f:
	f_csv = csv.reader(f)
	next(f_csv, None)
	for row in f_csv:
		temp.append([float(i) for i in row[0].split(';')])
		
temp = random.sample(temp,907)

temp = np.array(temp)

print(temp.shape)

# feature normalization (feature scaling)
X_scaler = StandardScaler()
temp = X_scaler.fit_transform(temp)

tsne = manifold.TSNE(n_components=1, init='pca', random_state=501)
x = tsne.fit_transform(temp[:,0:6])
print(x)

import csv
import numpy as np
from sklearn.pre