Topics Learnt Today:
1: Polynomial Regression: Polynomial regression is a type of regression analysis used when the relationship between the independent variable(s) and the dependent variable is not linear but can be approximated by a polynomial function.
- Polynomial regression allows for modeling non-linear relationships between variables by introducing higher-order terms (e.g., XSquare, XCube) into the regression equation.
2: Logistic Regression:
- Logistic regression is a type of regression analysis used for predicting binary or categorical outcomes. It’s used when the dependent variable is binary (e.g., 0/1, Yes/No, True/False).
- The logistic regression model uses the logistic (sigmoid) function to map the linear combination of independent variables to the probability of belonging to one of the categories.
3: Step Function:
- A step function, also known as a Heaviside step function or a unit step function, is a mathematical function that returns a constant value (usually 0 or 1) depending on whether its argument is greater than or equal to a threshold value.
- It’s often used in engineering and physics to model discontinuous changes or events. In binary classification problems, it’s sometimes used to represent binary outcomes.
4: State Function:
- A state function, in the context of state-space models, represents the internal state of a dynamic system. State-space models are commonly used in control theory, engineering, and various scientific fields.
- State-space models describe a system using two equations: the state equation (describing how the internal state evolves over time) and the measurement equation (relating the internal state to observed measurements).
- In control theory, state functions are used to represent variables such as position, velocity, and acceleration, and they are essential for designing control systems.