Machine learning sklearn library installation:
pip install numpy
pip install matplotlib
pip install scipy
pip install sklearn
注：直接利用anaconda软件，它是直接安装好了除sklearn库的其他库。
pip install scikit-image
regression dataset
# # 波士顿房价预测数据
# from sklearn.datasets import load_boston
# 利福尼亚住房数据集
from sklearn.datasets import fetch_california_housing
# 加载数据集
X, y = fetch_california_housing(return_X_y=True)
Classification dataset
# 鸢尾花数据集
from sklearn.datasets import load_iris
# 加载数据集
X, y = load_iris(return_X_y=True)
Data set segmentation
# 数据集切分
from sklearn.model_selection import train_test_split
# 训练集数据、测试集数据、训练集标签、测试集标签、 数据集分割为 80%训练 20%测试
X_train, X_test, y_train, y_test = train_test_split(X, y, train_size=0.2)
Model save and load
pip install joblib
keep:
# 保存：模型、模型保存的名字
joblib.dump(value=model, filename="model_knn")
load:
model = joblib.load(filename="model_knn")
# 就可以预测了