Python鸢尾花代码

# -*- coding: utf-8 -*-
"""
Created on Mon Jul 16 10:40:31 2018


@author: PIPI
"""
import pandas as pd
import mglearn
import numpy as np
from sklearn.datasets import load_iris
iris_dataset = load_iris()
print("keys of iris_dataset: \n{}".format(iris_dataset.keys()))
print(iris_dataset['DESCR'][:193]+"\n...")
print("Target names: {}".format(iris_dataset['target_names']))
print("Feature names: \n{}".format(iris_dataset['feature_names']))
print("Type of data: {}".format(type(iris_dataset['data'])))
print("Shape of data: {}".format(iris_dataset['data'].shape))
print("First five rows of data:\n{}".format(iris_dataset['data'][:5]))
print("Type of target: {}".format(type(iris_dataset['target'])))
print("Shape of target: {}".format(iris_dataset['target'].shape))
print("Target:\n{}".format(iris_dataset['target']))
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(iris_dataset['data'], iris_dataset['target'], random_state=0)
print("X_train shape: {}".format(X_train.shape))
print("y_train shape: {}".format(y_train.shape))
print("X_test shape: {}".format(X_test.shape))
print("y_test shape: {}".format(y_test.shape))


# 利用X_train中的数据创建DataFrame
# 利用iris_dataset.feature_names中的字符串对数据列进行标记
iris_dataframe = pd.DataFrame(X_train, columns=iris_dataset.feature_names)
# 利用DataFrame创建散点图矩阵，按y_train着色
grr = pd.scatter_matrix(iris_dataframe, c=y_train, figsize=(15, 15), marker='o',hist_kwds={'bins': 20}, s=60, alpha=.8, cmap=mglearn.cm3)
from sklearn.neighbors import KNeighborsClassifier
knn = KNeighborsClassifier(n_neighbors=1)
knn.fit(X_train, y_train)
X_new = np.array([[5, 2.9, 1, 0.2]])
print("X_new.shape: {}".format(X_new.shape))
prediction = knn.predict(X_new)
print("Prediction: {}".format(prediction))
print("Predicted target name: {}".format(iris_dataset['target_names'][prediction]))
y_pred = knn.predict(X_test)
print("Test set predictions:\n {}".format(y_pred))
print("Test set score: {:.2f}".format(np.mean(y_pred == y_test)))