AI Learning

Dataset

Iris

from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split

iris = load_iris()
df = pd.DataFrame(iris.data, columns=iris.feature_names)
df["label"] = iris.target
df.columns = [
    "sepal length", "sepal width", "petal length", "petal width", "label"
]

plt.scatter(df[:50]["sepal length"], df[:50]["sepal width"], label="0")
plt.scatter(df[50:100]["sepal length"], df[50:100]["sepal width"], label="1")
plt.xlabel("sepal length")
plt.ylabel("sepal width")
plt.legend()

data = np.array(df.iloc[:100, [0, 1, -1]])
X, y = data[:,:-1], data[:,-1]
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)