构建第一个模型:KNN算法(Iris_dataset) 利用鸢尾花数据集完成一个简单的机器学习应用~万丈高楼平地起,虽然很基础,但是还是跟着书敲了一遍代码。 一、模型构建流程 1、获取数据 本次实验的Iris数据集来自skicit-learn的datasets模块 from sklearn.datasetsimportload_irisiris_dataset=load_iris() 查看一下数据: 可以...
1. Load in the iris dataset which is split into a training and testing dataset 2. Do some basic exploratory analysis of the dataset and go through a scatterplot 3. Write out the algorithm for kNN WITHOUT using the sklearn package 4. Use the sklearn package to implement kNN and compare ...
'target_names': array(['setosa', 'versicolor', 'virginica'], dtype='<U10'), 'DESCR': '.. _iris_dataset:\n\nIris plants dataset\n---\n\n**Data Set Characteristics:**\n\n :Number of Instances: 150 (50 in each of three classes)\n :Number of Attributes: 4 numeric, predictive ...
Chaitanya Virmani · 3y ago· 132 views arrow_drop_up2 Copy & Edit11 more_vert Iris Dataset- KNNNotebookInputOutputLogsComments (0)Output Data An error occurred: Unexpected end of JSON input Download notebook output navigate_nextminimize content_copyhelpSyntaxError: Unexpected end of JSON input...
KNN算法文件:KnnAlgorithm.py # -*- coding: utf-8 -*- """ Created on Tue Jul 19 10:10:40 2022 @author: 文浩 """ import numpy as np def knn(inX,DataSet,Label,K): #欧几里得距离计算样本之间的相似度 dist = (((DataSet-inX)**2).sum(1))**0.5 ...
numpy as np # 同上iris数据集，前五个为blue类,中间5个为green类，最后5个为yellow类 dataset2 ...
邻居搜索算法的选择是通过关键字'algorithm'来控制的,它必须是['auto', 'ball_tree', 'kd_tree', 'brute']之一。当默认值'auto'时,算法尝试从训练数据中确定最佳方法。 更多参数详情请参见: https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html 实战案例 案例一 ...
A classic example of classification is the iris dataset, in which you use physical measurements of plants to predict their species. A famous algorithm that can be used for classification is logistic regression. Regression is a prediction task in which the target variable is numeric. A famous ...
knn分类irisknn分类算法案例 KNN算法相对于其他算法是一种特别好实现且易于理解的分类算法,主要根据不同特征之间的距离来进行分类。一般的分类算法首先要训练一个模型,然后用测试集检验模型,但是KNN算法不用训练模型,直接采用待测样本与训练样本的距离来实现分类。KNN基本原理:根据距离函数计算待分类样本X和每个训练样本的...
knn.fit(iris_X_train, iris_y_train) KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski', metric_params=None, n_jobs=1, n_neighbors=5, p=2, weights='uniform') knn.predict(iris_X_test)printiris_y_test KNeighborsClassifier方法中含有8个参数(以下前两个常用): ...