Composition design for (PrNd–La–Ce)<sub>2</sub>Fe<sub>14</sub>B melt-spun magnets by machine learning technique

Composition design for (PrNd–La–Ce)₂Fe₁₄B melt-spun magnets by machine learning technique

Li Rui^{1, 2}, Liu Yao^{1, 2}, Zuo Shu-Lan^{1, 2}, Zhao Tong-Yun^{1, 2}, Hu Feng-Xia^{1, 2}, Sun Ji-Rong^{1, 2}, Shen Bao-Gen^{1, 2, †}

Predicted scatter plots on the test dataset by the four modeling techniques, (a) linear regression, (b) Decision Trees Regression, (c) Support Vector Regression with a radial basis function kernel, and (d) Gradient Boosted Regression Trees. X axis and Y axis denote the measured and predicted values, respectively.