func (algo *LinearRegression) SaveModel(path string) { sb := util.StringBuilder{} for f, g := range algo.Model { sb.Int64(f) sb.Write("\t") sb.Float(g) sb.Write("\n") } sb.WriteToFile(path) }
func (lr *LROWLQN) SaveModel(path string) { sb := util.StringBuilder{} for key, val := range lr.Model.Data { sb.Int64(key) sb.Write("\t") sb.Float(val) sb.Write("\n") } sb.WriteToFile(path) }
func (self *LinearSVM) SaveModel(path string) { sb := util.StringBuilder{} for f, g := range self.w.Data { sb.Int64(f) sb.Write("\t") sb.Float(g) sb.Write("\n") } sb.WriteToFile(path) }
func (algo *EPLogisticRegression) SaveModel(path string) { sb := util.StringBuilder{} for f, g := range algo.Model { sb.Int64(f) sb.Write("\t") sb.Float(g.Mean) sb.Write("\t") sb.Float(g.Vari) sb.Write("\n") } sb.WriteToFile(path) }