Add feature analysis model card

README.md

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+---
+library_name: keras
+tags:
+  - keras
+  - tensorflow
+  - deep-learning
+  - feature-extraction
+  - dimensionality-reduction
+  - clustering
+  - computer-vision
+  - fire-detection
+  - fire-severity
+---
+
+# Fire Feature Analysis
+
+This repository contains trained models and generated artifacts from feature extraction, dimensionality reduction, representation learning, and clustering experiments performed as part of the fire detection and severity classification project.
+
+## Contents
+
+### Autoencoder
+`autoencoder_model_dimention_reduction.keras` — a trained Keras autoencoder used in the dimensionality-reduction workflow.
+
+### Autoencoder Latent Representations
+`autoencoder_latent_representations_dimention_reduction.npy` — latent representations generated by the autoencoder.
+
+### Autoencoder Losses
+`autoencoder_losses_tri_classification_dimention_reduction.npy` — loss values generated during the autoencoder experiment.
+
+### EfficientNet Feature Representations
+`efficientnet_features_tri_classification_feature_extraction.npy` — feature representations extracted using EfficientNet.
+
+### Fire Feature Representations
+`fire_features_effnet_tri_classification_feature_extraction.npy` — fire-related feature representations generated during the feature-extraction workflow.
+
+### SOM Clustering
+`som_tri_classification_clustering.npy` — output of the Self-Organizing Map (SOM) clustering experiment.
+
+## Loading the Autoencoder
+
+```python
+import tensorflow as tf
+
+autoencoder = tf.keras.models.load_model(
+    "autoencoder_model_dimention_reduction.keras"
+)
+
+autoencoder.summary()
+```
+
+## Loading the NumPy Artifacts
+
+```python
+import numpy as np
+
+latent_representations = np.load(
+    "autoencoder_latent_representations_dimention_reduction.npy"
+)
+
+losses = np.load(
+    "autoencoder_losses_tri_classification_dimention_reduction.npy"
+)
+
+som_results = np.load(
+    "som_tri_classification_clustering.npy"
+)
+```
+
+## Analysis Workflow
+
+The artifacts in this repository support experimentation involving:
+
+1. Deep feature extraction
+2. Representation learning
+3. Dimensionality reduction
+4. Latent-space analysis
+5. Feature analysis
+6. Clustering
+
+## Project Context
+
+This repository is part of a larger deep learning project containing:
+
+- binary fire detection models
+- fire severity classification models
+- datasets
+- notebooks
+- feature extraction
+- dimensionality reduction
+- clustering
+- recommendation generation
+
+## Limitations
+
+The generated NumPy artifacts are dependent on the original data preprocessing and model pipelines.
+
+To correctly interpret these artifacts, the corresponding project code and preprocessing procedures should also be considered.
+
+## License
+
+No standardized open-source license has been specified for this repository.
+
+Please refer to the original project and dataset terms before redistribution or commercial use.