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""" | |
A deep neural network with or w/o dropout in one file. | |
""" | |
import numpy | |
import theano | |
import sys | |
import math | |
from theano import tensor as T | |
from theano import shared |
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from sklearn.base import BaseEstimator, TransformerMixin | |
from sklearn.metrics.pairwise import rbf_kernel | |
class KMeansTransformer(BaseEstimator, TransformerMixin): | |
def __init__(self, centroids): | |
self.centroids = centroids | |
def fit(self, X, y=None): | |
return self |
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""" | |
Code for training RBMs with contrastive divergence. Tries to be as | |
quick and memory-efficient as possible while utilizing only pure Python | |
and NumPy. | |
""" | |
# Copyright (c) 2009, David Warde-Farley | |
# All rights reserved. | |
# | |
# Redistribution and use in source and binary forms, with or without |
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class OnlineLearner(object): | |
def __init__(self, **kwargs): | |
self.last_misses = 0. | |
self.iratio = 0. | |
self.it = 1. | |
self.l = kwargs["l"] | |
self.max_ratio = -np.inf | |
self.threshold = 500. | |
def hinge_loss(self, vector, cls, weight): |
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#include <opencv2/opencv.hpp> | |
#include <vector> | |
using namespace cv; | |
using namespace std; | |
int main () { | |
Mat img = imread("lena.jpg"); | |
CascadeClassifier cascade; | |
if (cascade.load("haarcascade_frontalface_alt.xml")) { |
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# Author: Kyle Kaster | |
# License: BSD 3-clause | |
import numpy as np | |
def online_stats(X): | |
""" | |
Converted from John D. Cook | |
http://www.johndcook.com/blog/standard_deviation/ | |
""" |
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