Different Machine learning algorithms are perfromed on kaggle leaf dataset for leaf classification purpose. The dataset consists of different species like:
- Cornus_Controversa
- Quercus_Pubescens
- Celtis_Koraiensis
- Acer_Platanoids
- Alnus_Maximowiczii
- etc.,
- Logistic regression
- K Nearest Neighbors
- Decision Tree
- Random Forest Classifier
- Gradient Boost
- Support Vector Machine
- Gaussian Naive Bayes
- Neural Networks
The random forest classifier provides nearly 97% of accurate results however, the single neural network also provide an accuracy rate of 98% in the classification process.