refactor: rename folder structure to sort for algorithms

ML/aufgaben/decisiontree/decisiontree_iris.py

@@ -0,0 +1,42 @@
+"""
+Use a decisiontree classifier to predict flowers based on sepal and petal features
+
+- This is an example of a supervised ML algorithm
+    - it has labels on the training data
+    - you tell the model: this is class X during training
+"""
+
+import matplotlib.pyplot as plt
+
+from sklearn import datasets
+from sklearn.tree import DecisionTreeClassifier
+from sklearn import tree
+
+# load the iris data set and look at its dimensions
+iris = datasets.load_iris()
+print(iris.data.size)
+print(iris.target.size)
+print(iris.feature_names)
+print(iris.target_names)
+
+# use a decition tree classifier
+classifier = DecisionTreeClassifier()
+# use all but the last sample for training
+classifier.fit(iris.data[:-1], iris.target[:-1])
+
+# use the model to predict the last data sample
+last_sample = iris.data[-1:]
+last_target = iris.target[-1:]
+print(f"predicted: {last_sample} vs real: {last_target}")
+
+# print the tree for visual inspection
+fig, ax = plt.subplots(figsize=(20, 10))
+tree.plot_tree(
+    classifier,
+    feature_names=iris.feature_names,
+    class_names=iris.target_names,
+    filled=True,
+    rounded=True,
+    ax=ax,
+)
+fig.savefig("decisiontree_iris.png", dpi=150, bbox_inches="tight")