Question
In this problem the Iris data set will be used. The Iris Plants Database contains 3 classes of 50 instances each, where each class refers
In this problem the Iris data set will be used. The Iris Plants Database contains 3 classes of 50 instances each, where each class refers to a type of Iris plant. Four attributes/features (in centimeters) were collected for each plant instance. A fifth attribute is provided which is the class label of the plant type.
(b) Develop a stack (not linked list) where the observations are stacked starting with the first observation using the sepal length feature. For example observation 1 with a value of 5.1 will be at the bottom of the stack. The choice is up to the developer, at a minimum use the first 10 observation. Show the pseudocode or code of your implementation (please use JAVA language) . Provide the running time of your code from reading in the data, storing the keys and linking the feature data.
For code please use JAVA language
Please download data from Iris.csv file or use this table
sepal_length | sepal_width | petal_length | petal_width | species |
5.1 | 3.5 | 1.4 | 0.2 | setosa |
4.9 | 3 | 1.4 | 0.2 | setosa |
4.7 | 3.2 | 1.3 | 0.2 | setosa |
4.6 | 3.1 | 1.5 | 0.2 | setosa |
5 | 3.6 | 1.4 | 0.2 | setosa |
5.4 | 3.9 | 1.7 | 0.4 | setosa |
4.6 | 3.4 | 1.4 | 0.3 | setosa |
5 | 3.4 | 1.5 | 0.2 | setosa |
4.4 | 2.9 | 1.4 | 0.2 | setosa |
4.9 | 3.1 | 1.5 | 0.1 | setosa |
5.4 | 3.7 | 1.5 | 0.2 | setosa |
4.8 | 3.4 | 1.6 | 0.2 | setosa |
4.8 | 3 | 1.4 | 0.1 | setosa |
4.3 | 3 | 1.1 | 0.1 | setosa |
5.8 | 4 | 1.2 | 0.2 | setosa |
5.7 | 4.4 | 1.5 | 0.4 | setosa |
5.4 | 3.9 | 1.3 | 0.4 | setosa |
5.1 | 3.5 | 1.4 | 0.3 | setosa |
5.7 | 3.8 | 1.7 | 0.3 | setosa |
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