README.md

---
datasets:
- your-username/quadratic-equations-dataset
tags:
- mathematics
- algebra
- quadratic-equations
- dataset
license: "mit"
---

# Quadratic Equations Dataset

## Dataset Summary
This dataset contains a collection of quadratic equations along with their solutions, discriminant values, root types, and step-by-step solutions. It is designed for training and evaluating machine learning models that solve quadratic equations.

## Supported Tasks and Leaderboards
- **Task**: Solving quadratic equations
- **Leaderboard**: Not applicable

## Languages
- **Mathematics**: The dataset is mathematical in nature with algebraic expressions in standard mathematical notation.

## Dataset Structure

### Data Fields
- `ID`: A unique identifier for each equation.
- `Equation`: The quadratic equation presented to the model.
- `Standard Form`: The equation rewritten in the standard form `ax^2 + bx + c = 0`.
- `Discriminant`: The value of the discriminant `Δ = b^2 - 4ac`, which determines the nature of the roots.
- `Roots`: The solutions to the quadratic equation.
- `Root Type`: The type of roots (real and distinct, real and repeated, or complex).
- `Solution Steps`: A detailed explanation of the steps to solve the quadratic equation.

### Data Splits
The dataset is divided into training, validation, and test sets:
- **Train**: Contains 80% of the data.
- **Validation**: Contains 10% of the data.
- **Test**: Contains 10% of the data.

### Example Data Point
```json
{
  "ID": 1,
  "Equation": "x^2 - 3x + 2 = 0",
  "Standard Form": "x^2 - 3x + 2 = 0",
  "Discriminant": 1,
  "Roots": ["x = 2", "x = 1"],
  "Root Type": "Real and Distinct",
  "Solution Steps": [
    "Identify a = 1, b = -3, c = 2.",
    "Calculate discriminant: Δ = (-3)^2 - 4(1)(2) = 1.",
    "Apply quadratic formula: x = (-(-3) ± √1)/(2(1)).",
    "Solve for x: x = 2, x = 1."
  ]
}