Advertising.csv

Signed-off-by: Darkstalker <allanw.mk@gmail.com>

Data/processed_advertising.csv

@@ -0,0 +1,201 @@
+TV,Radio,Newspaper,Sales
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Model_Library.py

@@ -48,7 +48,7 @@ def get_linear_config():
 
 
 def get_linear_regression_config():
-    """Get optimized configuration for a linear regression model."""
+    """Get configuration for a simple linear regression model."""
     return {
         "model": {
             "type": "regression",
@@ -57,29 +57,19 @@ def get_linear_regression_config():
             "task": "regression"
         },
         "training": {
-            "learning_rate": 0.01,
+            "learning_rate": 1,
             "epochs": 100,
-            "batch_size": 32,
-            "early_stopping": True,
-            "patience": 10
+            "batch_size": 32
         },
         "optimization": {
-            "optimizer": "adam",
-            "scheduler": "cosine",
-            "weight_decay": 0.001,
-            "min_lr": 1e-6,
-            "gradient_clip_val": 1.0,
-            "mixed_precision": True
+            "optimizer": "adam"
         },
         "data": {
             "batch_size": 32,
-            "num_workers": 7,
-            "pin_memory": True
+            "num_workers": 4
         },
         "logging": {
-            "tensorboard": True,
-            "log_every_n_steps": 10,
-            "metrics": ["mse", "r2"]
+            "tensorboard": False
         }
     }
 

Model_Types.py

@@ -1,7 +1,7 @@
 import torch
 import torch.nn as nn
 import pytorch_lightning as pl
-from visualization import NaiveBayesVisualizer, DecisionTreeVisualizer, KMeansVisualizer, LightGBMVisualizer, \
+from visualization import LinearRegressionVisualizer, LogisticRegressionVisualizer, NaiveBayesVisualizer, DecisionTreeVisualizer, KMeansVisualizer, LightGBMVisualizer, \
     RandomForestVisualizer, SVMVisualizer, GaussianMixtureVisualizer
 from typing import List, Dict, Any
 from torch.utils.data import TensorDataset, DataLoader

Train_Files/lightning_logs/version_0/hparams.yaml

@@ -0,0 +1,19 @@
+data:
+  batch_size: 32
+  num_workers: 4
+logging:
+  tensorboard: false
+model:
+  input_dim: 1
+  output_dim: 1
+  task: regression
+  type: linear_regression
+optimization:
+  optimizer: adam
+training:
+  accumulate_grad_batches: 2
+  batch_size: 16
+  epochs: 10
+  gradient_clip_val: 0.5
+  learning_rate: 0.01
+  max_steps: 100

Train_Files/lightning_logs/version_0/metrics.csv

@@ -0,0 +1,21 @@
+train_loss,epoch,mse,step,r2_score,val_loss
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+,9,178.84481811523438,99,-4.918807029724121,178.84481811523438

Train_Files/lightning_logs/version_1/hparams.yaml

@@ -0,0 +1,19 @@
+data:
+  batch_size: 32
+  num_workers: 4
+logging:
+  tensorboard: false
+model:
+  input_dim: 1
+  output_dim: 1
+  task: regression
+  type: linear_regression
+optimization:
+  optimizer: adam
+training:
+  accumulate_grad_batches: 2
+  batch_size: 16
+  epochs: 100
+  gradient_clip_val: 0.5
+  learning_rate: 0.01
+  max_steps: 100

Train_Files/lightning_logs/version_1/metrics.csv

@@ -0,0 +1,21 @@
+epoch,train_loss,mse,step,r2_score,val_loss
+0,274.9113464355469,274.9113464355469,9,-10.120745658874512,
+0,,205.5011749267578,9,-5.795079708099365,205.5011749267578
+1,196.35501098632812,196.35501098632812,19,-4.985584735870361,
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+9,,178.84481811523438,99,-4.918807029724121,178.84481811523438

Train_Files/lightning_logs/version_2/hparams.yaml

@@ -0,0 +1,19 @@
+data:
+  batch_size: 32
+  num_workers: 4
+logging:
+  tensorboard: false
+model:
+  input_dim: 1
+  output_dim: 1
+  task: regression
+  type: linear_regression
+optimization:
+  optimizer: adam
+training:
+  accumulate_grad_batches: 2
+  batch_size: 16
+  epochs: 100
+  gradient_clip_val: 0.5
+  learning_rate: 0.01
+  max_steps: 100

Train_Files/lightning_logs/version_2/metrics.csv

@@ -0,0 +1,21 @@
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+9,0,-10.120745658874512,274.9113464355469,274.9113464355469,
+9,0,-5.795079708099365,205.5011749267578,,205.5011749267578
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+99,9,-4.918807029724121,178.84481811523438,,178.84481811523438