Update README.md

README.md

@@ -1,90 +1,57 @@
----
-datasets:
-- Kaylah072001/Stock_Graphs_Dataset
-metrics:
-- accuracy
----
-stock_trend_analysis:
-  model:
-    architecture:
-      image_branch:
-        input_shape: [150, 150, 3]
-        layers:
-          - Conv2D_1:
-              filters: 32
-              kernel_size: [3, 3]
-              activation: relu
-          - MaxPooling2D_1:
-              pool_size: [2, 2]
-          - Conv2D_2:
-              filters: 64
-              kernel_size: [3, 3]
-              activation: relu
-          - MaxPooling2D_2:
-              pool_size: [2, 2]
-          - Conv2D_3:
-              filters: 128
-              kernel_size: [3, 3]
-              activation: relu
-          - MaxPooling2D_3:
-              pool_size: [2, 2]
-          - Flatten
+architecture:
+  image_branch:
+    input_shape: [150, 150, 3]
+    layers:
+      - Conv2D_1:
+          filters: 32
+          kernel_size: [3, 3]
+          activation: relu
+      - MaxPooling2D_1:
+          pool_size: [2, 2]
+      - Conv2D_2:
+          filters: 64
+          kernel_size: [3, 3]
+          activation: relu
+      - MaxPooling2D_2:
+          pool_size: [2, 2]
+      - Conv2D_3:
+          filters: 128
+          kernel_size: [3, 3]
+          activation: relu
+      - MaxPooling2D_3:
+          pool_size: [2, 2]
+      - Flatten
 
-      numerical_branch:
-        input_shape: [5]  # 5 technical indicators
-        layers:
-          - Dense:
-              units: 64
-              activation: relu
+  numerical_branch:
+    input_shape:   # 6 technical indicators
+    layers:
+      - Dense:
+          units: 64
+          activation: relu
 
-      combined_layers:
-        - Dense:
-            units: 128
-            activation: relu
-        - Dense:
-            units: 1
-            activation: sigmoid
+  combined_layers:
+    - Dense:
+        units: 128
+        activation: relu
+    - Dense:
+        units: 1
+        activation: sigmoid
+image_augmentation:
+  - rescale: 1./255
+  - rotation_range: 10
+  - width_shift_range: 0.1
+  - height_shift_range: 0.1
+  - zoom_range: 0.1
+  - horizontal_flip: true
 
-  data_generator:
-    class: CombinedDataGenerator
-    parameters:
-      batch_size: 32
-      img_size: [150, 150]
-      shuffle: true
-    
-    feature_extraction:
-      image_processing:
-        - grayscale_conversion
-        - edge_detection:
-            method: Canny
-            threshold1: 50
-            threshold2: 150
-        - line_detection:
-            method: HoughLinesP
-            min_line_length: 20
-            max_line_gap: 5
-
-      technical_indicators:
-        - slope:
-            method: polyfit
-            degree: 1
-        - volatility:
-            method: standard_deviation
-        - trend_strength:
-            method: mean_absolute_diff
-        - momentum:
-            method: price_difference
-            period: 10
-        - support_resistance:
-            method: min_max_difference
-
-  training:
-    optimizer: adam
-    loss: binary_crossentropy
-    metrics: [accuracy]
-
-  requirements:
-    - tensorflow
-    - opencv-python
-    - numpy
-    - scikit-learn
+technical_indicators:
+  - RSI:
+      method: ta.momentum.RSIIndicator
+  - MACD:
+      method: ta.trend.MACD
+  - Bollinger_Bands:
+      method: ta.volatility.BollingerBands
+  - ATR:
+      method: ta.volatility.AverageTrueRange
+  - OBV:
+      method: ta.volume.OnBalanceVolumeIndicator