Fix test data range and update training data splitting; enhance loggi…

…ng in IntervalData

 In `Algorithm`:
  - Changed test results loop from `(0..count)` to `(1..count)` to correct data indexing.
  - Modified training data generation to use only features and labels up to the start index instead of concatenating before and after slices.

- In `IntervalData`:
  - Consolidated multiple debug statements into a single line for clearer and more concise logging.

src/algorithm/algo.rs

@@ -75,20 +75,19 @@ impl Algorithm {
         let total_size = ds.len()?;
         let test_data_size = total_size / count;
 
-        let test_results: Vec<TestData> = (0..count)
+        let test_results: Vec<TestData> = (1..count)
             .map(|i| -> Result<TestData, KryptoError> {
                 let start = i * test_data_size;
                 let end = match i == count - 1 {
                     true => total_size,
                     false => (i + 1) * test_data_size,
                 };
                 let features = ds.get_features();
-                let labels = ds.get_labels();
                 let candles = ds.get_candles();
                 let test_features = &features[start..end];
                 let test_candles = &candles[start..end];
-                let train_features = [&features[..start], &features[end..]].concat();
-                let train_labels = [&labels[..start], &labels[end..]].concat();
+                let train_features = features[..start].to_vec();
+                let train_labels = ds.get_labels()[..start].to_vec();
 
                 let pls = get_pls(train_features, train_labels, settings.n)?;
                 let predictions = predict(&pls, test_features)?;

src/data/dataset.rs

@@ -183,9 +183,7 @@ impl IntervalData {
             .cloned()
             .collect();
 
-        debug!("Features shape: {}x{}", features.len(), features[0].len());
-        debug!("Labels count: {}", labels.len());
-        debug!("Candles count: {}", candles.len());
+        debug!("Features: {}x{} | Labels: {} | Candles: {}", features.len(), features[0].len(), labels.len(), candles.len());
 
         SymbolDataset::new(features, labels, candles)
     }