liblinear_multicore_svm_training_with_threaded_solver.py

1import sys
2import os
3
4# Ensure the liblinear path is in your sys.path if not installed via pip
5# from liblinear.liblinearutil import *
6
7from liblinearutil import train, predict, liblinear_read_problem
8
9# Sample data: labels and features (in dictionary format)
10y = [1, -1]
11x = [{1: 1, 2: 0.1}, {1: 0.2, 2: 1}]
12
13# To use the multicore version, specify a multicore-supported solver.
14# In LIBLINEAR, solvers like -s 1 (L2-regularized L2-loss SVC dual) 
15# or -s 2 (L2-regularized L2-loss SVC primal) are common.
16# Note: The 'multicore' version of LIBLINEAR typically implements 
17# parallelization at the C++ level for specific solvers (e.g., -s 1, 2, 3, 11).
18# Use the '-n' parameter to specify the number of threads (e.g., -n 4).
19
20options = '-s 1 -n 4'  # Solver type 1 with 4 threads
21
22# Train the model
23model = train(y, x, options)
24
25# Prepare test data
26test_y = [1]
27test_x = [{1: 1, 2: 0.2}]
28
29# Predict
30p_label, p_acc, p_val = predict(test_y, test_x, model)
31
32print(f"Predicted Label: {p_label}")