🧠 Reddit Niche Classifier

A lightweight feedforward neural network trained to classify Reddit posts into distinct niche categories such as advice, drama, humor, informative, and more — without relying on full NLP or raw text.

This model is designed to work with structured Reddit metadata, and is ideal for fast, low-cost deployment on classification tasks with tabular or engineered data.

✨ Model Details

Framework: TensorFlow / Keras
Input Features:
- Boolean indicators (e.g. contains_question, contains_capslock)
- Numeric metadata (e.g. score, num_comments, title_length, selftext_length, engagement_score)
- One-hot encoded subreddits
- Custom feature: num_caps_words
No raw text (title/selftext) is used

🏗️ Training Info

Architecture: [256, 128, 64] with ReLU activations
Output Layer: Dense(11) with softmax (multi-class classification)
Loss: sparse_categorical_crossentropy
Optimizer: Adam
Test Accuracy: ~67% on held-out set

📦 Usage

from tensorflow import keras
model = keras.models.load_model("niche_classifier_model")
predictions = model.predict(X_new)