Mushroom Classification

Keywords: Mushroom, Classfication

Background

Mushrooms are of two kinds, one is poisonous, and one is edible in nature, So, classification of mushrooms is a significant task to identify the edible mushrooms and to provide the same to customers to satisfy their hunger needs. The challenges identified in this dataset is that all the categories of all the columns are in short forms, to understand them, the author need to study the data card of the dataset, or the author renames all the categories into their original format. The method used to solve the edibility factors of the mushrooms is done through Artificial Neural Networks under deep learning. All the required libraries have been downloaded and all the features of the mushrooms have been preprocessed and then the ANN model was built upon them to predict. A four-layer ANN model was built involving both input and output layer. The accuracy of predictions of mushrooms came out to be 99 percent.

Aim & Objectives

Aim
To Classify the Mushroom Using DL Techniques
Objective
Develop an ANN to classify mushrooms,
Optimize ANN architecture for robustness, ensuring reliable classification of poisonous and edible mushrooms.
Enhance generalization by fine-tuning ANN hyperparameters, achieving consistent performance across diverse mushroom datasets.

Research Methodology

ANN Technique used

Software & Tools

Jupyter, Google Collab

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