深度学习代写_Algorithm 算法作业代写：Classification of Iris Plant

PBL Assignment 2: Classification of Iris Plant

Algorithm 算法作业代写 Iris data set is used to classify warblers. Each sample contains four features (the first 4 columns in the table below)

Requirement：Implement Decision trees and multi-layer Neural Networks to classify Iris plant.

Material submitted：  Algorithm 算法作业代写

1. Code and report；（email to：wushizhe@mail.dlut.edu.cn）


2. For each algorithm, testify different parameter settings；


3. Compare the performance of different algorithms, discuss their advantages/disadvantages

Data provided: Iris dataset

Iris dataset is a commonly used experimental data set in machine learning tasks, which was collected by Fisher in 1936. Iris is Anderson's iris data set in Chinese and Anderson's iris data set in English. Iris contains a total of 150 samples, which are divided into three categories. Each category contains 50 data, and each data contains 4 attributes. According to the four attributes of calyx length, calyx width, petal length and petal width, we can predict which kind of iris belongs to (setosa, versicolor, Virginia).

Iris data set is used to classify warblers. Each sample contains four features (the first 4 columns in the table below): calyx length, calyx width, petal length and petal width. We need to establish a classifier. The classifier can judge whether the sample belongs to Setosa, Versicolour or Virginia by the four features of the sample Which one of the irises is the classification problem in machine learning.

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