fix: wrong training procedure in SVM (#25)

* fix: wrong training procedure in SVM * ci(release): 1.1.0-beta.3 [skip ci] ## [1.1.0-beta.3](v1.1.0-beta.2...v1.1.0-beta.3) (2024-05-23) ### Bug Fixes * wrong training procedure in SVM ([74d1741](74d1741)) * ci(release): 1.1.1-beta.1 [skip ci] ## [1.1.1-beta.1](v1.1.0...v1.1.1-beta.1) (2024-05-23) ### Bug Fixes * wrong training procedure in SVM ([74d1741](74d1741)) ### CI * **release:** 1.1.0-beta.3 [skip ci] ([96988ac](96988ac)) --------- Co-authored-by: semantic-release-bot <semantic-release-bot@martynus.net>
f-aguzzi · May 23, 2024 · 7f25487 · 7f25487
1 parent 97d5deb
commit 7f25487
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diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,4 +1,16 @@
-## [1.1.0](https://github.com/f-aguzzi/tesi/compare/v1.0.0...v1.1.0) (2024-05-20)
+## [1.1.1-beta.1](https://github.com/f-aguzzi/tesi/compare/v1.1.0...v1.1.1-beta.1) (2024-05-23)
+
+
+### Bug Fixes
+
+* wrong training procedure in SVM ([74d1741](https://github.com/f-aguzzi/tesi/commit/74d1741743f53eea6cc2d9002005c6426bf4f0d0))
+
+
+### CI
+
+* **release:** 1.1.0-beta.3 [skip ci] ([96988ac](https://github.com/f-aguzzi/tesi/commit/96988acbfd0f015c03385f74f14ea26e98a9b4b2))
+
+## [1.1.0-beta.3](https://github.com/f-aguzzi/tesi/compare/v1.1.0-beta.2...v1.1.0-beta.3) (2024-05-23)
 
 
 ### Features
@@ -8,6 +20,9 @@
 
 ### Bug Fixes
 
+
+* wrong training procedure in SVM ([74d1741](https://github.com/f-aguzzi/tesi/commit/74d1741743f53eea6cc2d9002005c6426bf4f0d0))
+
 * add missing checks to LLDFSettings ([3d57752](https://github.com/f-aguzzi/tesi/commit/3d577527eefd0b183a66c378d53cb1f1ee506343)), closes [#20](https://github.com/f-aguzzi/tesi/issues/20)
 
 
@@ -26,6 +41,7 @@
 * **release:** 1.1.0-beta.1 [skip ci] ([2deffcc](https://github.com/f-aguzzi/tesi/commit/2deffcc4c8a29d09a4a644558e491d770f71f6dc)), closes [#7](https://github.com/f-aguzzi/tesi/issues/7)
 * **release:** 1.1.0-beta.2 [skip ci] ([25704dc](https://github.com/f-aguzzi/tesi/commit/25704dc4eb0cbc249bbf85611c5dfe257ebccc30)), closes [#20](https://github.com/f-aguzzi/tesi/issues/20) [#22](https://github.com/f-aguzzi/tesi/issues/22) [#23](https://github.com/f-aguzzi/tesi/issues/23)
 
+
 ## [1.1.0-beta.2](https://github.com/f-aguzzi/tesi/compare/v1.1.0-beta.1...v1.1.0-beta.2) (2024-05-20)
 
 

diff --git a/chemfusekit/svm.py b/chemfusekit/svm.py
@@ -3,14 +3,11 @@
 
 import pandas as pd
 
-import matplotlib.pyplot as plt
-import seaborn as sns
-
-from sklearn.model_selection import train_test_split
-from sklearn.metrics import confusion_matrix, classification_report
 from sklearn.svm import SVC
 
 from chemfusekit.lldf import LLDFModel
+from chemfusekit.__utils import run_split_test, print_confusion_matrix
+
 
 class SVMSettings:
     '''Holds the settings for the SVM object.'''
@@ -25,6 +22,7 @@ def __init__(self, kernel: str = 'linear', output: bool = False, test_split: boo
         self.output = output
         self.test_split = test_split
 
+
 class SVM:
     '''Class for Support Vector Machine analysis of the data'''
     def __init__(self, fused_data: LLDFModel, settings: SVMSettings):
@@ -35,22 +33,9 @@ def __init__(self, fused_data: LLDFModel, settings: SVMSettings):
     def svm(self):
         '''Performs Support Vector Machine analysis'''
 
-        x_data = self.fused_data.x_data
-        x_train = self.fused_data.x_train
-        y = self.fused_data.y
-
-        x_train, x_test, y_train, y_test = train_test_split(
-            x_data,
-            y,
-            train_size=0.7,
-            shuffle=True,
-            stratify=y
-        )
-
         # Linear kernel
         if self.settings.kernel == 'linear':
             svm_model = SVC(kernel='linear', probability=True)
-            # svmlinear.predict_proba(X_train)
         # Polynomial kernel
         elif self.settings.kernel == 'poly':
             svm_model = SVC(kernel='poly', degree=8)
@@ -61,40 +46,25 @@ def svm(self):
         elif self.settings.kernel == 'sigmoid':
             svm_model = SVC(kernel='sigmoid')
         else:
-            raise ValueError(f"SVM: this type of kernel does not exist ({self.settings.type=})")
+            raise ValueError(f"SVM: this type of kernel does not exist ({self.settings.kernel=})")
 
-        svm_model.fit(x_train, y_train)
+        svm_model.fit(self.fused_data.x_data, self.fused_data.y)
         self.model = svm_model
 
         if self.settings.output:
-            y_pred = svm_model.predict(x_test)
-
-            # Assuming 'y_true' and 'y_pred' are your true and predicted labels
-            cm = confusion_matrix(y_test, y_pred)
-
-            # Get unique class labels from y_true
-            class_labels = sorted(set(y_test))
-
-            # Plot the confusion matrix using seaborn with custom colormap (Blues)
-            sns.heatmap(
-                cm,
-                annot=True,
-                fmt='d',
-                cmap='Blues',
-                xticklabels=class_labels,
-                yticklabels=class_labels,
-                cbar=False,
-                vmin=0,
-                vmax=cm.max()
+            predictions = svm_model.predict(self.fused_data.x_data)
+            print_confusion_matrix(
+                self.fused_data.y,
+                predictions,
+                "Confusion matrix based on the whole data set"
             )
 
-            plt.xlabel('Predicted')
-            plt.ylabel('True')
-            plt.title('Confusion Matrix based on evaluation set')
-            plt.show()
-
-            # Print the classification report
-            print(classification_report(y_test, y_pred, digits=2))
+        if self.settings.output and self.settings.test_split:
+            run_split_test(
+                self.fused_data.x_data,
+                self.fused_data.y,
+                SVC(kernel=self.settings.kernel)
+            )
 
     def predict(self, x_data: pd.DataFrame):
         '''Performs SVM prediction once the model is trained'''

diff --git a/pyproject.toml b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "chemfusekit"
-version = "1.1.0"
+version = "1.1.1b1"
 description = "A minimal Python / Jupyter Notebook / Colab library for data fusion and chemometrical analysis."
 authors = [
     { name = "Federico Aguzzi", email = "62149513+f-aguzzi@users.noreply.github.com" }