Question 1(Clustering): Consider the following Iris dataset with 150 points, and each point has four
numerical features, as shown in the second to the fifth columns (sepal_length to petal_width), and
one categorical feature, as shown in the last column. The categorical feature is named "species"
with three possible categories: Iris Setosa, Iris Versicolour, and Iris Virginica. We only use the four
numerical features for the clustering task described below and ignore the categorical feature.Apply
the following three clustering methods: k-means, hierarchical clustering, and Gaussian mixture
models (GMM), to the Iris dataset and generate k clusters. (a) Choosing an appropriate number of
clusters for the dataset using the SSE-based technique and the kmeans method introduced in
class. (b) For each method, show a scatter plot of the clusters in the space spanned by the first
two numerical features, in which the data points belonging to each cluster are shown in a different
color. The following is a scatter plot of the dataset in the first two features, in which the three
different colors are related to three different categorical values. Figure 2: Scatter plot of the
dataset using the true class labels.
Question 1Clustering Consider the following Iris dataset .pdf
1. Question 1(Clustering): Consider the following Iris dataset with 150 points, and each point has four
numerical features, as shown in the second to the fifth columns (sepal_length to petal_width), and
one categorical feature, as shown in the last column. The categorical feature is named "species"
with three possible categories: Iris Setosa, Iris Versicolour, and Iris Virginica. We only use the four
numerical features for the clustering task described below and ignore the categorical feature.Apply
the following three clustering methods: k-means, hierarchical clustering, and Gaussian mixture
models (GMM), to the Iris dataset and generate k clusters. (a) Choosing an appropriate number of
clusters for the dataset using the SSE-based technique and the kmeans method introduced in
class. (b) For each method, show a scatter plot of the clusters in the space spanned by the first
two numerical features, in which the data points belonging to each cluster are shown in a different
color. The following is a scatter plot of the dataset in the first two features, in which the three
different colors are related to three different categorical values. Figure 2: Scatter plot of the
dataset using the true class labels
