Quantum Memristor Data

该数据集用于训练机器学习模型，旨在预测单量子忆阻器及耦合量子忆阻器的形态因子。数据按照2:1的比例分为训练集和测试集，为了提高计算速度，机器学习模型采用了LightGBM算法进行训练。该任务的目标是使用机器学习技术预测量子忆阻器的形态因子。

This dataset is used for training machine learning models, aiming to predict the figure of merit of single quantum memristors and coupled quantum memristors. The dataset is split into training and test sets at a ratio of 2:1, and the LightGBM algorithm was adopted to train the machine learning models to improve computational speed. The goal of this task is to predict the figure of merit of quantum memristors using machine learning techniques.