lambday

lambday

TEST(CrossValidationMMD, biased_full)
{
	const int32_t seed = 5;
	const index_t n=24;
	const index_t m=15;
	const index_t dim=2;
	const index_t num_null_samples=5;
	const index_t num_folds=3;
	const index_t num_runs=2;
	const index_t num_kernels=4;

lambday

// Type your code here, or load an example.
#include <vector>
#include <algorithm>
#include <numeric>
#include <cimmintrin>

using std::vector;
using std::iota;
using std::accumulate;

lambday

#include <iostream>
#include <shogun/base/init.h>
#include <shogun/lib/config.h>
#include <shogun/lib/SGMatrix.h>
#include <shogun/base/some.h>
#include <shogun/io/streaming/StreamingFileFromDenseFeatures.h>
#include <shogun/features/DenseFeatures.h>
#include <shogun/features/streaming/generators/MeanShiftDataGenerator.h>
#include <shogun/kernel/GaussianKernel.h>
#include <shogun/statistical_testing/QuadraticTimeMMD.h>

lambday

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Maths... Why give a s#!t"
   ]
  },
  {

lambday

#include <map>
#include <iostream>
#include <functional>
#include <tuple>
#include <memory>
#include <initializer_list>
#include <utility>

namespace std
{

lambday

train_feats = sg.RealSparseFeatures('../train.dat')
test_feats = sg.RealSparseFeatures('../test.dat')
train_labels = sg.RealDenseLabels('../train_labels.dat')

gammas = np.arange(1, 10)

lda = sg.LDA()
lda.preprocessor_chain().enque(sg.DimensionSubset()).enque(sg.NormOne()).enque(sg.FisherLDA())

params = sg.ModelSelectionParameters()

lambday

main:
        mov     eax, 409114
        ret

lambday

# your code goes here
gen_p = GaussianBlobsDataGenerator(...)
gen_q = GaussianBlobsDataGenerator(...)

mmd = QuadraticTimeMMD(gen_p, gen_q)
mmd.set_kernel(GaussianKernel(10, 2**0.5))
mmd.set_num_samples_p(1000)
mmd.set_num_samples_q(1000)

mmd.enable_watching()

lambday