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翻译scikit-learn Cookbook

学习sklearn

专栏作者

78

文章

52843

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15

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数据结构学习-python实现-数据排序--0412

谢尔排序是将数据一分为二的不断递归，让分开的两部分位置相对应的两个值比较大小，从而达到每个部分都是相对的顺序排列，而归并排序是分治策略，分为分裂和合并两个过程。耗费了额外的存储空间。

到不了的都叫做远方

2020-04-12

3270

数据结构学习-python实现-数据排序--0411

数据为何要排序？首先想到的是排序的数据能够更加便于观察，并更好的使用查找算法，降低复杂度。

到不了的都叫做远方

2020-04-11

3340

数据结构学习-python实现-数据查找--0410

数据查找算法的实质是数据的比对。 1.确定基本步骤 2.步骤足够简单，并反复执行。 3.查找次数介于1和n之间，平均为n/2，算法复杂度为O(n) # 无序表的顺序查找 def sequentialsearch(alist, item): pos = 0 found = False while pos < len(alist) and not found: # 退出while循环的两种方式 if alist[pos] == item: fo

到不了的都叫做远方

2020-04-10

3140

数据结构学习-python实现03--0403

1.必须有一个基本结束的条件！ 2.必须可改变状态，向着结束条件演进！ 3.必须是通过调用自身！

到不了的都叫做远方

2020-04-04

2160

数据结构学习-python实现02--0402

编程算法 node.js

今日继续进行了队列及单链表的学习。一、队列，先进先出的有序结构。基础代码如下： # 基本队列的代码 class Queue: def __init__(self): self.items = [] def isEmpty(self): return self.items == [] def enqueue(self, item): self.items.insert(0, item)

到不了的都叫做远方

2020-04-02

3680

数据结构学习-python实现01--0401

编程算法机器学习神经网络深度学习人工智能

经过近两年多的转行自学，乱七八糟的学了不少的东西，依然没有走到自己想要去的方向，继续学习，努力吧！

到不了的都叫做远方

2020-04-01

4400

Feature selection特征选择

This recipe along with the two following it will be centered around automatic feature selection. I like to think of this as the feature analogue of parameter tuning. In the same way that we cross-validate to find an appropriately general parameter, we can find an appropriately general subset of features. This will involve several different methods.

到不了的都叫做远方

2019-12-18

9070

Regression model evaluation回归模型评估

We learned about quantifying the error in classification, now we'll discuss quantifying the error for continuous problems. For example, we're trying to predict an age, not a gender.

到不了的都叫做远方

2019-12-18

6040

Stratified k-fold K-fold分层

编程算法 javascript

In this recipe, we'll quickly look at stratified k-fold valuation. We've walked through different recipes where the class representation was unbalanced in some manner. Stratified k-fold is nice because its scheme is specifically designed to maintain the class proportions.

到不了的都叫做远方

2019-12-16

8840

Label propagation with semi-supervised learning半监督学习之标签传播算法

Label propagation is a semi-supervised technique that makes use of the labeled and unlabeled data to learn about the unlabeled data. Quite often, data that will benefit from a classification algorithm is difficult to label. For example, labeling data might be very expensive, so only a subset is cost-effective to manually label. This said, there does seem to be slow, but growing, support for companies to hire taxonomists.

到不了的都叫做远方

2019-12-07

1.6K0

Tuning a random forest model调试随机森林模型

网络安全编程算法

In the previous recipe, we reviewed how to use the random forest classifier. In this recipe,we'll walk through how to tune its performance by tuning its parameters.

到不了的都叫做远方

2019-12-01

1.3K0

Defining the Gaussian process object directly直接定义高斯过程对象

python 编程算法

We just touched the surface of Gaussian processes. In this recipe, we'll look at how we can directly access the Gaussian process object with the correlation function we want.

到不了的都叫做远方

2019-11-08

3220

Binarizing label features二值化标签特征

In this recipe, we'll look at working with categorical variables in a different way. In the event that only one or two categories of the feature are important, it might be wise to avoid the extra dimensionality, which might be created if there are several categories.

到不了的都叫做远方

2019-10-29

7850

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