PDai Analytics Package

Overview

PDai (Predictive Data Analytics Intelligence) is a comprehensive R package designed for AI-powered predictive analytics and data insights. It provides core functionality for statistical modeling, machine learning workflows, and advanced data analysis tasks.

Features

• Predictive Modeling: Advanced algorithms for regression, classification, and time series forecasting
• Data Processing: Efficient data manipulation and transformation utilities
• Statistical Analysis: Comprehensive statistical testing and inference tools
• Visualization: Built-in plotting functions for data exploration and model diagnostics
• AI Integration: Seamless integration with modern AI/ML frameworks

Installation

From GitHub

# Install devtools if not already installed
if (!require(devtools)) {
  install.packages("devtools")
}

# Install PDai from GitHub
devtools::install_github("embeddedlayers/package-PDai")

Development Version

# Clone the repository
git clone https://github.com/embeddedlayers/package-PDai.git

# Install from local directory
devtools::install("package-PDai")

Quick Start

# Load the package
library(PDai)

# Example: Basic predictive analysis
data <- load_sample_data()
model <- pdai_predict(data, target = "outcome")
summary(model)

# Generate insights
insights <- generate_insights(model)
print(insights)

Main Functions

• pdai_predict(): Automated predictive modeling with best model selection
• pdai_classify(): Classification tasks with multiple algorithm options
• pdai_cluster(): Unsupervised clustering analysis
• pdai_timeseries(): Time series analysis and forecasting
• generate_insights(): AI-powered insights generation
• validate_model(): Comprehensive model validation and diagnostics

Documentation

Detailed documentation for each function is available through R's help system:

?pdai_predict
?generate_insights

Requirements

• R (>= 4.0.0)
• Dependencies are automatically installed with the package

Database Integration

For PostgreSQL integration and enterprise features, see our companion package PDaiPostgres.

Contributing

We welcome contributions! Please see our Contributing Guidelines for details on how to submit pull requests, report issues, and contribute to documentation.

Support

• Issues: GitHub Issues
• Email: support@embeddedlayers.com
• Documentation: Package Documentation

License

This project is licensed under the MIT License - see the LICENSE file for details.

Citation

If you use PDai in your research, please cite:

@software{pdai2024,
  title = {PDai: AI-Powered Predictive Analytics for R},
  author = {PeopleDrivenAI LLC},
  year = {2024},
  url = {https://github.com/embeddedlayers/package-PDai}
}

Related Projects

• MCP Analytics: Professional statistical analysis tools for Claude/Cursor
• PDaiPostgres: PostgreSQL integration for PDai

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Part of the EmbeddedLayers Analytics Ecosystem