Iris dataset classification python code
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Fitbit versa gps without phoneThe dataset we are going to use for this example is the famous Iris database of plant classification. In this dataset, we have 150 plant samples and four measurements of each: sepal length, sepal width, petal length, and petal width (all in centimeters). This classic dataset (first used in 1936!) is one of the classic datasets for data mining ... Feature Iris-setosa Iris-versicolor Iris-virginica sepal length 5.01 5.94 6.59 sepal width 3.42 2.77 2.97 petal length 1.46 4.26 5.55 petal width 0.24 1.33 2.03 Finally, here is a quick code that computes the class distribution for another dataset: Monte carlo risk analysis excel template
Dec 27, 2019 · X = pd.DataFrame (iris.data, columns = iris.feature_names) y = pd.Categorical.from_codes (iris.target, iris.target_names) Since the target variable is a categorical one consisting of 3 categories of flower species, we have used ‘Categorical.from_codes’. This constructor is useful when we have categories datatype.

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Iris dataset classification python code

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Iris dataset classification python code

Iris dataset classification python code

Iris dataset classification python code

Iris dataset classification python code

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Iris dataset classification python code

Iris dataset classification python code

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Iris dataset classification python code

Iris dataset classification python code

Iris dataset classification python code

Iris dataset classification python code



Iris dataset classification python code

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Iris dataset classification python code

Iris dataset classification python code

Iris dataset classification python code

Iris dataset classification python code

Iris dataset classification python code