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Computational Estimation by Scientific Data Mining with Classical Methods to Automate Learning Strategies of Scientists
ACM Transactions on Knowledge Discovery from Data
Experimental results are often plotted as 2-dimensional graphical plots (aka graphs) in scientific domains depicting dependent versus independent variables to aid visual analysis of processes. Repeatedly performing laboratory experiments consumes significant time and resources, motivating the need for computational estimation. The goals are to estimate the graph obtained in an experiment given its input conditions, and to estimate the conditions that would lead to a desired graph. Existingdoi:10.1145/3502736 fatcat:knjd4iuwxnakbmkx4l6ej3njj4