KeironO

{"Nigeria": {
            "Kaduna": [
                "Birni-Gwari",
                "Chikun",
                "Giwa",
                "Igabi",
                "Ikara",
                "jaba",
                "Jema'a",
                "Kachia",

KeironO

{"Ru": {"isotopic_weight": [95.907598, 97.905287, 98.9059393, 99.9042197, 100.9055822, 101.9043495, 103.90543], "atomic number": 44, "atomic_charge": 3, "isotopic_ratio": [0.0554, 0.0187, 0.1276, 0.126, 0.1706, 0.3155, 0.1862]}, "Re": {"isotopic_weight": [184.9529557, 186.9557508], "atomic number": 75, "atomic_charge": 2, "isotopic_ratio": [0.374, 0.626]}, "Rf": {"isotopic_weight": [261.0], "atomic number": 104, "atomic_charge": 0, "isotopic_ratio": [1.0]}, "Ra": {"isotopic_weight": [226.0], "atomic number": 88, "atomic_charge": 2, "isotopic_ratio": [1.0]}, "Rb": {"isotopic_weight": [84.9117893, 86.9091835], "atomic number": 37, "atomic_charge": 1, "isotopic_ratio": [0.7217, 0.2783]}, "Rn": {"isotopic_weight": [220.0], "atomic number": 86, "atomic_charge": 0, "isotopic_ratio": [1.0]}, "Rh": {"isotopic_weight": [102.905504], "atomic number": 45, "atomic_charge": 2, "isotopic_ratio": [1.0]}, "Be": {"isotopic_weight": [9.0121821], "atomic number": 4, "atomic_charge": 2, "isotopic_ratio": [1.0]}, "Ba": {"isotopic

KeironO

/usr/bin/python2.7 /home/keiron/.projects/lethality_prediction/python_files/wormbase_predict.py
Using Theano backend.
Loading the dataset...
	- Loading the raw dataset from ../data/Worm_Dropshilla_Lethality.arff
	- Vectorising the raw dataset into a format suitable for Neural Networks
	- Randomly shuffling the dataset, to ensure proper results
	- Splitting the dataset into separate training and testing sets
Now for the Deep Learning bit...
	- Modelling the Neural Network
	- Training the model

KeironO

/usr/lib/jvm/java-1.7.0-openjdk-amd64/bin/java -Xmx8192m -Didea.launcher.port=7533 -Didea.launcher.bin.path=/usr/share/jetbrains/intellij-idea/bin -Dfile.encoding=UTF-8 -classpath /usr/lib/jvm/java-1.7.0-openjdk-amd64/jre/lib/rt.jar:/usr/lib/jvm/java-1.7.0-openjdk-amd64/jre/lib/jce.jar:/usr/lib/jvm/java-1.7.0-openjdk-amd64/jre/lib/compilefontconfig.jar:/usr/lib/jvm/java-1.7.0-openjdk-amd64/jre/lib/charsets.jar:/usr/lib/jvm/java-1.7.0-openjdk-amd64/jre/lib/jsse.jar:/usr/lib/jvm/java-1.7.0-openjdk-amd64/jre/lib/rhino.jar:/usr/lib/jvm/java-1.7.0-openjdk-amd64/jre/lib/management-agent.jar:/usr/lib/jvm/java-1.7.0-openjdk-amd64/jre/lib/javazic.jar:/usr/lib/jvm/java-1.7.0-openjdk-amd64/jre/lib/resources.jar:/usr/lib/jvm/java-1.7.0-openjdk-amd64/jre/lib/ext/sunpkcs11.jar:/usr/lib/jvm/java-1.7.0-openjdk-amd64/jre/lib/ext/icedtea-sound.jar:/usr/lib/jvm/java-1.7.0-openjdk-amd64/jre/lib/ext/sunjce_provider.jar:/usr/lib/jvm/java-1.7.0-openjdk-amd64/jre/lib/ext/localedata.jar:/usr/lib/jvm/java-1.7.0-openjdk-amd64/jre/lib/e

KeironO

tch, so far we have updates of size: 0 out of 4
INFO  [2015-03-14 06:01:55,966] org.deeplearning4j.iterativereduce.actor.multilayer.MasterActor: Current jobs left [Job{workerId='localhost-39b19f91-7947-4e7c-ac7c-5623b9430cdf', work=null}, Job{workerId='localhost-32713b6c-95eb-4113-88d2-24dc10bea9cf', work=null}, Job{workerId='localhost-1ecd1364-f558-4975-a3ab-f43e4a347be6', work=null}, Job{workerId='localhost-636a3a50-289a-4148-93b7-d5f7cadcbfaf', work=null}]
INFO  [2015-03-14 06:02:02,740] org.deeplearning4j.iterativereduce.actor.multilayer.ActorNetworkRunner: State tracker not done...blocking
INFO  [2015-03-14 06:02:05,965] org.deeplearning4j.iterativereduce.actor.multilayer.MasterActor: Status check on next iteration
INFO  [2015-03-14 06:02:05,966] org.deeplearning4j.iterativereduce.actor.multilayer.MasterActor: Still waiting on next batch, so far we have updates of size: 0 out of 4
INFO  [2015-03-14 06:02:05,966] org.deeplearning4j.iterativereduce.actor.multilayer.MasterActor: Current jobs left [Job{worke

KeironO

package org.deeplearning4j.eunice;


import org.apache.commons.math3.random.MersenneTwister;
import org.apache.commons.math3.random.RandomGenerator;
import org.deeplearning4j.datasets.fetchers.BaseDataFetcher;
import org.deeplearning4j.datasets.vectorizer.ImageVectorizer;
import org.deeplearning4j.datasets.vectorizer.Vectorizer;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.dataset.DataSet;