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)
}