using namespace 数学工具构造器;

self.steps 0 ['categorical_encoding', <autosklearn.pipeline.components.data_preprocessing.one_hot_encoding.OHEChoice object at 0x7f7a74dfa8d0>] 1 ['imputation', Imputation(random_state=None, str...

https://borgwang.github.io/ml/2019/07/28/gaussian-processes.html http://www.gaussianprocess.org/gpml/chapters/RW.pdf http://www.columbia.edu/~jwp2128/Teaching/E6892/papers/mlss2012_cunningham_gaussian...

# coding:utf-8 import numpy as np import matplotlib.pyplot as plt from sklearn.neighbors import KernelDensity np.random.seed(1) N = 20 X = np.concatenate((np.random.normal(0, 1,int( 0.3 * N)), ...

文章目录概率计算算法 概率计算算法 import numpy as np # 状态集合 Q={0,1,2} # 观测集合 V={0,1} red=0 white=1 # 状态转移 A = np.array([ [.5, .2, .3], [.3, .5, .2], [.2, .3, .5], ]) # 发射概率 (状态 -> 观测) B = np.array([ ...

n=20 m=2 X=np.random.randn(n,m) def kmeans(X,h,min_err=0.000001,max_iter=1000000000): n,m=X.shape err,iter=1,1 c0=X[:h,:] while True: clusters=[np.zeros([0,m]) for i in range(...

ImageNet数据集预处理：如果一个图片的长宽比例小于一定比值，则直接拉伸。如果大于一定比值，按照 左、中、右 三部分进行切割 def process(img,max_ratio=1.35): if len(img.shape)==2: img=cv2.cvtColor(img,cv2.COLOR_GRAY2RGB) h,w,_=img.shape r...