Enhancing Photovoltaic Module Fault Diagnosis with Unmanned Aerial Vehicles and Deep Learning-Based Image Analysis

Table 8

Brief summary about various types of classifiers.

Classifier	Description
Tree-based classifiers	Tree-based classification models are a form of supervised machine learning method that divides training data into subsets using a sequence of conditional statements. Each consecutive split increases the model’s complexity, which may then be utilised to generate predictions.
Bayes-based classifiers	A statistical method of inference known as Bayesian classification uses probability to convey uncertainty about the connection being learned and is founded on a distinctive concept of what it means to learn from data.
Lazy-based classifiers	Lazy-based classifier models collect cases during training and do no meaningful work until classification. The training sample is distinguished from the test sample by using a lower Euclidean distance in which the equivalent condition is assumed to be the training samples [37].