Project struct

src/learning/ml.py

@@ -0,0 +1,41 @@
+from abc import ABC, abstractmethod
+from learning.data import Dataset
+
+import numpy as np
+
+
+class MLAlgorithm(ABC):
+
+    dataset: Dataset
+    testset: np.ndarray
+    learnset: np.ndarray
+
+    def _set_dataset(self, dataset:Dataset, split:float=0.2):
+        ndarray = dataset.shuffle().as_ndarray()
+        split = int(ndarray.shape[0] * split)
+
+        self.dataset = dataset
+        self.testset = ndarray[split:]
+        self.learnset = ndarray[:split]
+
+    def _split_data_target(self, dset:np.ndarray) -> tuple[np.ndarray, np.ndarray, int]:
+        x = np.delete(dset, 0, 1)
+        y = dset[:, 0]
+        m = dset.shape[0]
+        return (x, y, m)
+
+    def learn(self, times:int) -> tuple[list, list]:
+        train = []
+        test = []
+        for _ in range(0, max(1, times)):
+            train.append(self.learning_step())
+            test.append(self.test_error())
+        return (train, test)
+
+    @abstractmethod
+    def learning_step(self) -> float:
+        pass
+
+    @abstractmethod
+    def test_error(self) -> float:
+        pass