func main() {
// /home/jwh/dataset/rcv1/rcv1_train.binary
var train_file_name string
var test_file_name string
var lambda float64
flag.StringVar(&train_file_name, "train", "", "training file (libsvm format)")
flag.StringVar(&test_file_name, "test", "", "testing file (libsvm format)")
flag.Float64Var(&lambda, "lambda", 0.000001, "trade-off parameter")
if len(os.Args) <= 3 {
fmt.Printf("Usage: \n")
flag.PrintDefaults()
os.Exit(0)
}
flag.Parse()
start := time.Now()
p, _ := readData.ReadData(train_file_name, false)
p.Lambda = float32(lambda)
p.Epsilon = 0.0001
p.PrintProblem()
solve_lasso_CD(p)
elapsed := time.Since(start)
fmt.Printf("took %s \n", elapsed)
p_test, _ := readData.ReadData(test_file_name, false)
p_test.X = p.X
fmt.Printf("testing...\n")
loss_test := get_acc_as_reg(p_test)
fmt.Printf("testing error: %e\n", loss_test)
}
func main() {
fmt.Printf("logistic_regression only supports binary classification for now\n")
var train_file_name string
var test_file_name string
var lambda float64
flag.StringVar(&train_file_name, "train", "", "training file (libsvm format)")
flag.StringVar(&test_file_name, "test", "", "testing file (libsvm format)")
flag.Float64Var(&lambda, "lambda", 0.000001, "trade-off parameter")
var cpuprofile = flag.String("cpuprofile", "", "write cpu profile to file")
if len(os.Args) <= 3 {
fmt.Printf("Usage: \n")
flag.PrintDefaults()
os.Exit(0)
}
flag.Parse()
//for profiling
if *cpuprofile != "" {
f, err := os.Create(*cpuprofile)
if err != nil {
log.Fatal(err)
}
pprof.StartCPUProfile(f)
defer pprof.StopCPUProfile()
}
start := time.Now()
p, _ := readData.ReadData(train_file_name, true)
elapsed := time.Since(start)
fmt.Printf("took %s to read data \n", elapsed)
p.PrintProblem()
p.Lambda = float32(lambda)
p.Epsilon = 0.001
start = time.Now()
// solver.Solve_lr_CD(p) // glmnet method
var sigma float32
var r float32
sigma = 0.8
r = 0.8
solver.Solve_lr_new_glmnet_cdn(p, sigma, r) //newGLMNET, can be speeded up by using more tricks
elapsed = time.Since(start)
fmt.Printf("took %s to train \n", elapsed)
start = time.Now()
p_test, _ := readData.ReadData(train_file_name, true)
p_test.X = p.X
fmt.Printf("testing... ")
loss_test := get_acc(p_test)
fmt.Printf("acc: %f\n", loss_test)
elapsed = time.Since(start)
fmt.Printf("took %s to test \n", elapsed)
}
func main() {
fmt.Printf("logistic_regression only supports binary classification for now\n")
var train_file_name string
var test_file_name string
var lambda float64
var alg_type int
flag.StringVar(&train_file_name, "train", "", "training file (libsvm format)")
flag.StringVar(&test_file_name, "test", "", "testing file (libsvm format)")
flag.Float64Var(&lambda, "lambda", 0.0000001, "positive weight constant (default 0.000001)")
flag.IntVar(&alg_type, "a", 1, "algorithm (1=lasso, 2=logitic regresion, 3 = find min lambda for all zero solution)")
var cpuprofile = flag.String("cpuprofile", "", "write cpu profile to file")
// if len(os.Args) <= 3 {
// fmt.Printf("Usage: \n")
// flag.PrintDefaults()
// os.Exit(0)
// }
flag.Parse()
//for profiling
if *cpuprofile != "" {
f, err := os.Create(*cpuprofile)
if err != nil {
log.Fatal(err)
}
pprof.StartCPUProfile(f)
defer pprof.StopCPUProfile()
}
start := time.Now()
train_file_name = "/home/jwh/dataset/rcv1/rcv1_train.binary"
alg_type = 1
p, _ := readData.ReadData(train_file_name, true)
readData.FeatureNormalize(p) //normalize feature
elapsed := time.Since(start)
fmt.Printf("took %s to read data \n", elapsed)
p.PrintProblem()
p.Lambda = float32(lambda)
p.Epsilon = 0.00001
p.Max_iter = 5000
start = time.Now()
if alg_type == 1 {
solver.Solve_lasso_with_scd(p)
} else if alg_type == 2 {
} else if alg_type == 3 {
} else {
//error
}
// solver.Solve_lr_new_glmnet_cdn(p, sigma, r) //newGLMNET, can be speeded up by using more tricks
elapsed = time.Since(start)
fmt.Printf("took %s to train \n", elapsed)
start = time.Now()
// p_test, _ := readData.ReadData(train_file_name, true)
// p_test.X = p.X
// fmt.Printf("testing... ")
// loss_test := get_acc(p_test)
// fmt.Printf("acc: %f\n", loss_test)
// elapsed = time.Since(start)
// fmt.Printf("took %s to test \n", elapsed)
}