def converter_kernellocallylinearembedding_modular(data_fname, k): try: from modshogun import RealFeatures, KernelLocallyLinearEmbedding, LinearKernel, CSVFile features = RealFeatures(CSVFile(data_fname)) kernel = LinearKernel() converter = KernelLocallyLinearEmbedding(kernel) converter.set_target_dim(1) converter.set_k(k) converter.apply(features) return features except ImportError: print('No Eigen3 available')
def embed(filename='words.dat'): print 'loading' words = [] with open(filename) as f: words.extend([str.rstrip() for str in f.readlines()]) print 'loaded', words converter = KernelLocallyLinearEmbedding() converter.set_k(20) converter.set_target_dim(2) converter.parallel.set_num_threads(1) embedding = converter.embed_kernel(word_kernel(words)).get_feature_matrix() return embedding, words
def converter_kernellocallylinearembedding_modular (data_fname,k): try: from modshogun import RealFeatures, KernelLocallyLinearEmbedding, LinearKernel, CSVFile features = RealFeatures(CSVFile(data_fname)) kernel = LinearKernel() converter = KernelLocallyLinearEmbedding(kernel) converter.set_target_dim(1) converter.set_k(k) converter.apply(features) return features except ImportError: print('No Eigen3 available')
def embed(filename='words.dat'): print 'loading' words = [] with open(filename) as f: words.extend([str.rstrip() for str in f.readlines()]) print 'loaded', words converter = KernelLocallyLinearEmbedding() converter.set_k(20) converter.set_target_dim(2) converter.parallel.set_num_threads(1) embedding = converter.embed_kernel(word_kernel(words)).get_feature_matrix() return embedding,words