Incremental PCA
Rahul Gupta
rahulgupta100689 at gmail.com
Sat Apr 18 05:56:22 EDT 2020
i wanted to implement incremental PCA.
Got this code for stack overflow but i am wondering what y = chunk.pop("y") does and what is this argument "y" to pop
from sklearn.decomposition import IncrementalPCA
import csv
import sys
import numpy as np
import pandas as pd
dataset = sys.argv[1]
chunksize_ = 5 * 25000
dimensions = 300
reader = pd.read_csv(dataset, sep = ',', chunksize = chunksize_)
sklearn_pca = IncrementalPCA(n_components=dimensions)
for chunk in reader:
y = chunk.pop("Y")
sklearn_pca.partial_fit(chunk)
# Computed mean per feature
mean = sklearn_pca.mean_
# and stddev
stddev = np.sqrt(sklearn_pca.var_)
Xtransformed = None
for chunk in pd.read_csv(dataset, sep = ',', chunksize = chunksize_):
y = chunk.pop("Y")
Xchunk = sklearn_pca.transform(chunk)
if Xtransformed == None:
Xtransformed = Xchunk
else:
Xtransformed = np.vstack((Xtransformed, Xchunk))
More information about the Python-list
mailing list