# abhishek2305995/california_housing_price_prediction_using_machine_learning architecture

> Architecture diagram of the GitHub repository abhishek2305995/california_housing_price_prediction_using_machine_learning, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-30). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/abhishek2305995/california_housing_price_prediction_using_machine_learning
- Repository: https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning

## Overview

This is a California housing machine-learning project with a Streamlit interface for entering housing features and receiving a price estimate, a value category, and a cluster-based region label. The sampled app shows the runtime inference path and loads regression, classification, and clustering artifacts. The README also documents model training/evaluation capabilities—SVM, PCA, neural networks, and algorithm comparison—but their implementation details are not present in the sampled source. The graph represents those as documented project capabilities rather than asserting unverified runtime connections.

Main entry points: [`app.py`](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/app.py) (Predict Action), [`regression_model.pkl`](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/regression_model.pkl) (Price Regression), [`kmeans_model.pkl`](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/kmeans_model.pkl) (KMeans Regions), [`scaler.pkl`](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/scaler.pkl) (Feature Scaler)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_app["Streamlit Application"]
  node_inputs["Feature Inputs<br/>[app.py]"]
  node_model_choice["Model Choice<br/>[app.py]"]
  node_predict_action["Predict Action<br/>[app.py]"]
  node_results["Prediction Results<br/>[app.py]"]
end

subgraph group_runtime["Prediction Runtime"]
  node_scaler["Feature Scaler<br/>[scaler.pkl]"]
  node_regression["Price Regression"]
  node_classification["Value Classification<br/>[app.py]"]
  node_logistic["Logistic Model<br/>[logistic_model.pkl]"]
  node_decision_tree["Decision Tree"]
  node_cluster_scaler["Cluster Scaler<br/>[cluster_scaler.pkl]"]
  node_kmeans["KMeans Regions<br/>[kmeans_model.pkl]"]
end

subgraph group_modeling["Modeling Capabilities"]
  node_svm["SVM Comparison<br/>[ADL_PROJECT.ipynb]"]
  node_pca["PCA Clustering<br/>[ADL_PROJECT.ipynb]"]
  node_neural_network["Neural Network"]
  node_model_evaluation["Model Evaluation<br/>[ADL_PROJECT.ipynb]"]
end

node_user(("Housing User"))

node_user -->|"enters features"| node_inputs
node_user -->|"selects model"| node_model_choice
node_user -->|"requests prediction"| node_predict_action
node_predict_action -->|"scales features"| node_scaler
node_predict_action -->|"predicts price"| node_regression
node_predict_action -->|"selects and predicts"| node_classification
node_classification -->|"uses when selected"| node_logistic
node_classification -->|"uses when selected"| node_decision_tree
node_predict_action -->|"scales for clustering"| node_cluster_scaler
node_predict_action -->|"predicts cluster"| node_kmeans
node_predict_action -->|"displays predictions"| node_results
node_model_choice -->|"chooses classifier"| node_classification
node_regression -->|"supplies price"| node_results
node_classification -->|"supplies category"| node_results
node_kmeans -->|"supplies region"| node_results

click node_inputs "https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/app.py"
click node_model_choice "https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/app.py"
click node_predict_action "https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/app.py"
click node_scaler "https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/scaler.pkl"
click node_regression "https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/regression_model.pkl"
click node_classification "https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/app.py"
click node_logistic "https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/logistic_model.pkl"
click node_decision_tree "https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/decision_tree_model.pkl"
click node_cluster_scaler "https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/cluster_scaler.pkl"
click node_kmeans "https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/kmeans_model.pkl"
click node_results "https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/app.py"
click node_svm "https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/ADL_PROJECT.ipynb"
click node_pca "https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/ADL_PROJECT.ipynb"
click node_neural_network "https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/neural_network_model.pkl"
click node_model_evaluation "https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/ADL_PROJECT.ipynb"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_inputs,node_model_choice,node_predict_action,node_results,node_user toneBlue
class node_scaler,node_regression,node_classification,node_logistic,node_decision_tree,node_cluster_scaler,node_kmeans toneAmber
class node_svm,node_pca,node_neural_network,node_model_evaluation toneMint
```

## Components

### Streamlit Application

- [Feature Inputs](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/app.py): `app.py`
- [Model Choice](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/app.py): `app.py`
- [Predict Action](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/app.py): `app.py`
- [Prediction Results](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/app.py): `app.py`

### Prediction Runtime

- [Feature Scaler](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/scaler.pkl): `scaler.pkl`
- [Price Regression](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/regression_model.pkl): `regression_model.pkl`
- [Value Classification](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/app.py): `app.py`
- [Logistic Model](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/logistic_model.pkl): `logistic_model.pkl`
- [Decision Tree](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/decision_tree_model.pkl): `decision_tree_model.pkl`
- [Cluster Scaler](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/cluster_scaler.pkl): `cluster_scaler.pkl`
- [KMeans Regions](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/kmeans_model.pkl): `kmeans_model.pkl`

### Modeling Capabilities

- [SVM Comparison](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/ADL_PROJECT.ipynb): `ADL_PROJECT.ipynb`
- [PCA Clustering](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/ADL_PROJECT.ipynb): `ADL_PROJECT.ipynb`
- [Neural Network](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/neural_network_model.pkl): `neural_network_model.pkl`
- [Model Evaluation](https://github.com/abhishek2305995/california_housing_price_prediction_using_machine_learning/blob/main/ADL_PROJECT.ipynb): `ADL_PROJECT.ipynb`

### Other components

- **Housing User**

## Connections

- Housing User → Feature Inputs: enters features (evidence: `app.py`)
- Housing User → Model Choice: selects model (evidence: `app.py`)
- Housing User → Predict Action: requests prediction (evidence: `app.py`)
- Predict Action → Feature Scaler: scales features (evidence: `app.py`)
- Predict Action → Price Regression: predicts price (evidence: `app.py`)
- Predict Action → Value Classification: selects and predicts (evidence: `app.py`)
- Value Classification → Logistic Model: uses when selected (evidence: `app.py`)
- Value Classification → Decision Tree: uses when selected (evidence: `app.py`)
- Predict Action → Cluster Scaler: scales for clustering (evidence: `app.py`)
- Predict Action → KMeans Regions: predicts cluster (evidence: `app.py`)
- Predict Action → Prediction Results: displays predictions (evidence: `app.py`)
- Model Choice → Value Classification: chooses classifier (evidence: `app.py`)
- Price Regression → Prediction Results: supplies price (evidence: `app.py`)
- Value Classification → Prediction Results: supplies category (evidence: `app.py`)
- KMeans Regions → Prediction Results: supplies region (evidence: `app.py`)