IoT-Enabled Intelligent System for the Radiation Monitoring and Warning Approach

Algorithm 1

Adaptive boosting classifier.

	Input: Input data to N, number of iterations M
	Choice of the loss function , choice of the base learner model h (x, θ)
	Output: Powerful classifier
	Step 1: Initialize weights: (start with the null classifier )
	Step 2: Iterate the function from t = 1 to M for generating the training dataset by sampling
	Step 3: Fit some weak learners .
	Step 4: Update the weights and get a new base learner function for better results.
	Step 5: Find the best gradient-descent stepsize pt
	Pt = argminp
	Step 4: Output the final model