Frank Taylor Tachyon5
Tachyon5
/ LSTMService.java
Created
February 9, 2018 14:47
EMA example: it's only called LSTM for the moment
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| package ch.algotrader.strategy; | |
| import java.math.BigDecimal; | |
| import org.springframework.stereotype.Component; | |
| import org.apache.log4j.LogManager; | |
| import org.joda.time.DateTime; | |
| import org.joda.time.Period; | |
| import ch.algotrader.entity.marketData.BarVO; |
Tachyon5
/ DBNMnistFullExample.java
Last active
February 24, 2016 18:05
Can you explain the .hiddenUnit and .visibleUnit attributes?
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| package org.deeplearning4j.examples.deepbelief; | |
| import org.deeplearning4j.datasets.iterator.DataSetIterator; | |
| import org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator; | |
| import org.deeplearning4j.eval.Evaluation; | |
| import org.deeplearning4j.nn.api.OptimizationAlgorithm; | |
| import org.deeplearning4j.nn.conf.GradientNormalization; | |
| import org.deeplearning4j.nn.conf.MultiLayerConfiguration; | |
| import org.deeplearning4j.nn.conf.NeuralNetConfiguration; | |
| import org.deeplearning4j.nn.conf.layers.OutputLayer; |
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| MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder() | |
| .seed(seed) | |
| .gradientNormalization(GradientNormalization.ClipElementWiseAbsoluteValue) | |
| .gradientNormalizationThreshold(1.0) | |
| .iterations(iterations) | |
| .momentum(0.5) | |
| .momentumAfter(Collections.singletonMap(3, 0.9)) | |
| .optimizationAlgo(OptimizationAlgorithm.CONJUGATE_GRADIENT) | |
| .list(4) | |
| .layer(0, new RBM.Builder().nIn(numRows*numColumns).nOut(500) |
Tachyon5
/ StackedAutoEncoderMnistExample.javaStackedAutoEncoderMnistExample.java
Created
February 18, 2016 19:42
I want to add a HistogramIterationListener to the following but can't seem to get the UI running.
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| package org.deeplearning4j.examples.autoencoder; | |
| import org.deeplearning4j.datasets.iterator.DataSetIterator; | |
| import org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator; | |
| import org.deeplearning4j.eval.Evaluation; | |
| import org.deeplearning4j.nn.api.OptimizationAlgorithm; | |
| import org.deeplearning4j.nn.conf.GradientNormalization; | |
| import org.deeplearning4j.nn.conf.MultiLayerConfiguration; | |
| import org.deeplearning4j.nn.conf.NeuralNetConfiguration; | |
| import org.deeplearning4j.nn.conf.layers.AutoEncoder; |
Tachyon5
/ generative.py
Last active
August 29, 2015 14:24
— forked from jakevdp/generative.py
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| """ | |
| Bayesian Generative Classifier | |
| ------------------------------ | |
| """ | |
| # Author: Jake Vanderplas <jakevdp@cs.washington.edu> | |
| import numpy as np | |
| from sklearn.neighbors.kde import KernelDensity | |
| from sklearn.mixture import GMM | |
| from sklearn.base import BaseEstimator, clone |
Tachyon5
/ sklearn-lr-spark.py
Created
July 10, 2014 19:19
— forked from MLnick/sklearn-lr-spark.py
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| import sys | |
| from pyspark.context import SparkContext | |
| from numpy import array, random as np_random | |
| from sklearn import linear_model as lm | |
| from sklearn.base import copy | |
| N = 10000 # Number of data points | |
| D = 10 # Numer of dimensions | |
| ITERATIONS = 5 |