tinysklearn
仿制了部分sklearn接口,结构简单,容易理解,非常适合机器学习入门
使用方法
- 安装
pip install tinysklearn
- 使用
使用方法和sklearn是一致的(至少实现了fit,predict,transform,score这四种方法)
from tinysklearn.tinysklearn import LinearRegression
from tinysklearn.datasets import load_boston
from tinysklearn.preprocessing import StandardScaler
from tinysklearn.neighbors import KNeighborsClassifier
from tinysklearn.model_selection import train_test_split
from tinysklearn.decomposition import PCA
from tinysklearn.metrics import mean_absolute_error
#读取数据
boston = load_boston()
x = boston.data
y = boston.target
#分割训练集测试集
x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state=666666)
#构建模型,训练
lr = LinearRegression()
lr.fit(x_train, x_test)
#预测
lr.predict(x_test)
#评估
lr.score(x_test, y_test)
Metadata
Release files for tinysklearn 0.0.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| tinysklearn-0.0.3.tar.gz | 5.4 kB | Details |
Release files / tinysklearn-0.0.3.tar.gz
| Download URL | tinysklearn-0.0.3.tar.gz |
|---|---|
| Size | 5.4 kB |
| Tags | Source |
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twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.6.9
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