commit dccb0e360740e815ea680d730430a59faee2b11f Author: Laurent Date: Tue Mar 17 21:28:37 2026 +0100 Initial commit diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..1fac4d5 --- /dev/null +++ b/.gitignore @@ -0,0 +1,43 @@ +.gradle +build/ +!gradle/wrapper/gradle-wrapper.jar +!**/src/main/**/build/ +!**/src/test/**/build/ +.kotlin + +### IntelliJ IDEA ### +.idea/modules.xml +.idea/jarRepositories.xml +.idea/compiler.xml +.idea/libraries/ +*.iws +*.iml +*.ipr +out/ +!**/src/main/**/out/ +!**/src/test/**/out/ + +### Eclipse ### +.apt_generated +.classpath +.factorypath +.project +.settings +.springBeans +.sts4-cache +bin/ +!**/src/main/**/bin/ +!**/src/test/**/bin/ + +### NetBeans ### +/nbproject/private/ +/nbbuild/ +/dist/ +/nbdist/ +/.nb-gradle/ + +### VS Code ### +.vscode/ + +### Mac OS ### +.DS_Store \ No newline at end of file diff --git a/.idea/.gitignore b/.idea/.gitignore new file mode 100644 index 0000000..ab1f416 --- /dev/null +++ b/.idea/.gitignore @@ -0,0 +1,10 @@ +# Default ignored files +/shelf/ +/workspace.xml +# Ignored default folder with query files +/queries/ +# Datasource local storage ignored files +/dataSources/ +/dataSources.local.xml +# Editor-based HTTP Client requests +/httpRequests/ diff --git a/.idea/gradle.xml b/.idea/gradle.xml new file mode 100644 index 0000000..14746e7 --- /dev/null +++ b/.idea/gradle.xml @@ -0,0 +1,16 @@ + + + + + + \ No newline at end of file diff --git a/.idea/misc.xml b/.idea/misc.xml new file mode 100644 index 0000000..f16dea7 --- /dev/null +++ b/.idea/misc.xml @@ -0,0 +1,10 @@ + + + + + + + + + + \ No newline at end of file diff --git a/build.gradle.kts b/build.gradle.kts new file mode 100644 index 0000000..d65d34b --- /dev/null +++ b/build.gradle.kts @@ -0,0 +1,20 @@ +plugins { + id("java") +} + +group = "be.naaturel" +version = "1.0-SNAPSHOT" + +repositories { + mavenCentral() +} + +dependencies { + testImplementation(platform("org.junit:junit-bom:5.10.0")) + testImplementation("org.junit.jupiter:junit-jupiter") + testRuntimeOnly("org.junit.platform:junit-platform-launcher") +} + +tasks.test { + useJUnitPlatform() +} \ No newline at end of file diff --git a/gradle/wrapper/gradle-wrapper.jar b/gradle/wrapper/gradle-wrapper.jar new file mode 100644 index 0000000..249e583 Binary files /dev/null and b/gradle/wrapper/gradle-wrapper.jar differ diff --git a/gradle/wrapper/gradle-wrapper.properties b/gradle/wrapper/gradle-wrapper.properties new file mode 100644 index 0000000..4fb93d2 --- /dev/null +++ b/gradle/wrapper/gradle-wrapper.properties @@ -0,0 +1,6 @@ +#Tue Mar 17 15:36:58 CET 2026 +distributionBase=GRADLE_USER_HOME +distributionPath=wrapper/dists +distributionUrl=https\://services.gradle.org/distributions/gradle-9.0.0-bin.zip +zipStoreBase=GRADLE_USER_HOME +zipStorePath=wrapper/dists diff --git a/gradlew b/gradlew new file mode 100644 index 0000000..1b6c787 --- /dev/null +++ b/gradlew @@ -0,0 +1,234 @@ +#!/bin/sh + +# +# Copyright © 2015-2021 the original authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +############################################################################## +# +# Gradle start up script for POSIX generated by Gradle. +# +# Important for running: +# +# (1) You need a POSIX-compliant shell to run this script. If your /bin/sh is +# noncompliant, but you have some other compliant shell such as ksh or +# bash, then to run this script, type that shell name before the whole +# command line, like: +# +# ksh Gradle +# +# Busybox and similar reduced shells will NOT work, because this script +# requires all of these POSIX shell features: +# * functions; +# * expansions «$var», «${var}», «${var:-default}», «${var+SET}», +# «${var#prefix}», «${var%suffix}», and «$( cmd )»; +# * compound commands having a testable exit status, especially «case»; +# * various built-in commands including «command», «set», and «ulimit». +# +# Important for patching: +# +# (2) This script targets any POSIX shell, so it avoids extensions provided +# by Bash, Ksh, etc; in particular arrays are avoided. +# +# The "traditional" practice of packing multiple parameters into a +# space-separated string is a well documented source of bugs and security +# problems, so this is (mostly) avoided, by progressively accumulating +# options in "$@", and eventually passing that to Java. +# +# Where the inherited environment variables (DEFAULT_JVM_OPTS, JAVA_OPTS, +# and GRADLE_OPTS) rely on word-splitting, this is performed explicitly; +# see the in-line comments for details. +# +# There are tweaks for specific operating systems such as AIX, CygWin, +# Darwin, MinGW, and NonStop. +# +# (3) This script is generated from the Groovy template +# https://github.com/gradle/gradle/blob/master/subprojects/plugins/src/main/resources/org/gradle/api/internal/plugins/unixStartScript.txt +# within the Gradle project. +# +# You can find Gradle at https://github.com/gradle/gradle/. +# +############################################################################## + +# Attempt to set APP_HOME + +# Resolve links: $0 may be a link +app_path=$0 + +# Need this for daisy-chained symlinks. +while + APP_HOME=${app_path%"${app_path##*/}"} # leaves a trailing /; empty if no leading path + [ -h "$app_path" ] +do + ls=$( ls -ld "$app_path" ) + link=${ls#*' -> '} + case $link in #( + /*) app_path=$link ;; #( + *) app_path=$APP_HOME$link ;; + esac +done + +APP_HOME=$( cd "${APP_HOME:-./}" && pwd -P ) || exit + +APP_NAME="Gradle" +APP_BASE_NAME=${0##*/} + +# Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script. +DEFAULT_JVM_OPTS='"-Xmx64m" "-Xms64m"' + +# Use the maximum available, or set MAX_FD != -1 to use that value. +MAX_FD=maximum + +warn () { + echo "$*" +} >&2 + +die () { + echo + echo "$*" + echo + exit 1 +} >&2 + +# OS specific support (must be 'true' or 'false'). +cygwin=false +msys=false +darwin=false +nonstop=false +case "$( uname )" in #( + CYGWIN* ) cygwin=true ;; #( + Darwin* ) darwin=true ;; #( + MSYS* | MINGW* ) msys=true ;; #( + NONSTOP* ) nonstop=true ;; +esac + +CLASSPATH=$APP_HOME/gradle/wrapper/gradle-wrapper.jar + + +# Determine the Java command to use to start the JVM. +if [ -n "$JAVA_HOME" ] ; then + if [ -x "$JAVA_HOME/jre/sh/java" ] ; then + # IBM's JDK on AIX uses strange locations for the executables + JAVACMD=$JAVA_HOME/jre/sh/java + else + JAVACMD=$JAVA_HOME/bin/java + fi + if [ ! -x "$JAVACMD" ] ; then + die "ERROR: JAVA_HOME is set to an invalid directory: $JAVA_HOME + +Please set the JAVA_HOME variable in your environment to match the +location of your Java installation." + fi +else + JAVACMD=java + which java >/dev/null 2>&1 || die "ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH. + +Please set the JAVA_HOME variable in your environment to match the +location of your Java installation." +fi + +# Increase the maximum file descriptors if we can. +if ! "$cygwin" && ! "$darwin" && ! "$nonstop" ; then + case $MAX_FD in #( + max*) + MAX_FD=$( ulimit -H -n ) || + warn "Could not query maximum file descriptor limit" + esac + case $MAX_FD in #( + '' | soft) :;; #( + *) + ulimit -n "$MAX_FD" || + warn "Could not set maximum file descriptor limit to $MAX_FD" + esac +fi + +# Collect all arguments for the java command, stacking in reverse order: +# * args from the command line +# * the main class name +# * -classpath +# * -D...appname settings +# * --module-path (only if needed) +# * DEFAULT_JVM_OPTS, JAVA_OPTS, and GRADLE_OPTS environment variables. + +# For Cygwin or MSYS, switch paths to Windows format before running java +if "$cygwin" || "$msys" ; then + APP_HOME=$( cygpath --path --mixed "$APP_HOME" ) + CLASSPATH=$( cygpath --path --mixed "$CLASSPATH" ) + + JAVACMD=$( cygpath --unix "$JAVACMD" ) + + # Now convert the arguments - kludge to limit ourselves to /bin/sh + for arg do + if + case $arg in #( + -*) false ;; # don't mess with options #( + /?*) t=${arg#/} t=/${t%%/*} # looks like a POSIX filepath + [ -e "$t" ] ;; #( + *) false ;; + esac + then + arg=$( cygpath --path --ignore --mixed "$arg" ) + fi + # Roll the args list around exactly as many times as the number of + # args, so each arg winds up back in the position where it started, but + # possibly modified. + # + # NB: a `for` loop captures its iteration list before it begins, so + # changing the positional parameters here affects neither the number of + # iterations, nor the values presented in `arg`. + shift # remove old arg + set -- "$@" "$arg" # push replacement arg + done +fi + +# Collect all arguments for the java command; +# * $DEFAULT_JVM_OPTS, $JAVA_OPTS, and $GRADLE_OPTS can contain fragments of +# shell script including quotes and variable substitutions, so put them in +# double quotes to make sure that they get re-expanded; and +# * put everything else in single quotes, so that it's not re-expanded. + +set -- \ + "-Dorg.gradle.appname=$APP_BASE_NAME" \ + -classpath "$CLASSPATH" \ + org.gradle.wrapper.GradleWrapperMain \ + "$@" + +# Use "xargs" to parse quoted args. +# +# With -n1 it outputs one arg per line, with the quotes and backslashes removed. +# +# In Bash we could simply go: +# +# readarray ARGS < <( xargs -n1 <<<"$var" ) && +# set -- "${ARGS[@]}" "$@" +# +# but POSIX shell has neither arrays nor command substitution, so instead we +# post-process each arg (as a line of input to sed) to backslash-escape any +# character that might be a shell metacharacter, then use eval to reverse +# that process (while maintaining the separation between arguments), and wrap +# the whole thing up as a single "set" statement. +# +# This will of course break if any of these variables contains a newline or +# an unmatched quote. +# + +eval "set -- $( + printf '%s\n' "$DEFAULT_JVM_OPTS $JAVA_OPTS $GRADLE_OPTS" | + xargs -n1 | + sed ' s~[^-[:alnum:]+,./:=@_]~\\&~g; ' | + tr '\n' ' ' + )" '"$@"' + +exec "$JAVACMD" "$@" diff --git a/gradlew.bat b/gradlew.bat new file mode 100644 index 0000000..107acd3 --- /dev/null +++ b/gradlew.bat @@ -0,0 +1,89 @@ +@rem +@rem Copyright 2015 the original author or authors. +@rem +@rem Licensed under the Apache License, Version 2.0 (the "License"); +@rem you may not use this file except in compliance with the License. +@rem You may obtain a copy of the License at +@rem +@rem https://www.apache.org/licenses/LICENSE-2.0 +@rem +@rem Unless required by applicable law or agreed to in writing, software +@rem distributed under the License is distributed on an "AS IS" BASIS, +@rem WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +@rem See the License for the specific language governing permissions and +@rem limitations under the License. +@rem + +@if "%DEBUG%" == "" @echo off +@rem ########################################################################## +@rem +@rem Gradle startup script for Windows +@rem +@rem ########################################################################## + +@rem Set local scope for the variables with windows NT shell +if "%OS%"=="Windows_NT" setlocal + +set DIRNAME=%~dp0 +if "%DIRNAME%" == "" set DIRNAME=. +set APP_BASE_NAME=%~n0 +set APP_HOME=%DIRNAME% + +@rem Resolve any "." and ".." in APP_HOME to make it shorter. +for %%i in ("%APP_HOME%") do set APP_HOME=%%~fi + +@rem Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script. +set DEFAULT_JVM_OPTS="-Xmx64m" "-Xms64m" + +@rem Find java.exe +if defined JAVA_HOME goto findJavaFromJavaHome + +set JAVA_EXE=java.exe +%JAVA_EXE% -version >NUL 2>&1 +if "%ERRORLEVEL%" == "0" goto execute + +echo. +echo ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH. +echo. +echo Please set the JAVA_HOME variable in your environment to match the +echo location of your Java installation. + +goto fail + +:findJavaFromJavaHome +set JAVA_HOME=%JAVA_HOME:"=% +set JAVA_EXE=%JAVA_HOME%/bin/java.exe + +if exist "%JAVA_EXE%" goto execute + +echo. +echo ERROR: JAVA_HOME is set to an invalid directory: %JAVA_HOME% +echo. +echo Please set the JAVA_HOME variable in your environment to match the +echo location of your Java installation. + +goto fail + +:execute +@rem Setup the command line + +set CLASSPATH=%APP_HOME%\gradle\wrapper\gradle-wrapper.jar + + +@rem Execute Gradle +"%JAVA_EXE%" %DEFAULT_JVM_OPTS% %JAVA_OPTS% %GRADLE_OPTS% "-Dorg.gradle.appname=%APP_BASE_NAME%" -classpath "%CLASSPATH%" org.gradle.wrapper.GradleWrapperMain %* + +:end +@rem End local scope for the variables with windows NT shell +if "%ERRORLEVEL%"=="0" goto mainEnd + +:fail +rem Set variable GRADLE_EXIT_CONSOLE if you need the _script_ return code instead of +rem the _cmd.exe /c_ return code! +if not "" == "%GRADLE_EXIT_CONSOLE%" exit 1 +exit /b 1 + +:mainEnd +if "%OS%"=="Windows_NT" endlocal + +:omega diff --git a/settings.gradle.kts b/settings.gradle.kts new file mode 100644 index 0000000..9069b4f --- /dev/null +++ b/settings.gradle.kts @@ -0,0 +1 @@ +rootProject.name = "ANN" \ No newline at end of file diff --git a/src/main/java/com/naaturel/ANN/Main.java b/src/main/java/com/naaturel/ANN/Main.java new file mode 100644 index 0000000..8b21bf4 --- /dev/null +++ b/src/main/java/com/naaturel/ANN/Main.java @@ -0,0 +1,57 @@ +package com.naaturel.ANN; + +import com.naaturel.ANN.domain.abstraction.Neuron; +import com.naaturel.ANN.domain.model.dataset.DataSet; +import com.naaturel.ANN.domain.model.dataset.DataSetEntry; +import com.naaturel.ANN.domain.model.dataset.Label; +import com.naaturel.ANN.domain.model.neuron.Bias; +import com.naaturel.ANN.domain.model.neuron.Input; +import com.naaturel.ANN.domain.model.neuron.Synapse; +import com.naaturel.ANN.domain.model.neuron.Weight; +import com.naaturel.ANN.implementation.activationFunction.Heaviside; +import com.naaturel.ANN.implementation.activationFunction.Linear; +import com.naaturel.ANN.implementation.neuron.SimplePerceptron; +import com.naaturel.ANN.implementation.training.GradientDescentTraining; + +import java.util.*; + +public class Main { + + public static void main(String[] args){ + + DataSet dataSet = new DataSet(Map.ofEntries( + Map.entry(new DataSetEntry(List.of(1.0F, 6.0F)), new Label(1.0F)), + Map.entry(new DataSetEntry(List.of(7.0F, 9.0F)), new Label(-1.0F)), + Map.entry(new DataSetEntry(List.of(1.0F, 9.0F)), new Label(1.0F)), + Map.entry(new DataSetEntry(List.of(7.0F, 10.0F)), new Label(-1.0F)), + Map.entry(new DataSetEntry(List.of(2.0F, 5.0F)), new Label(-1.0F)), + Map.entry(new DataSetEntry(List.of(2.0F, 7.0F)), new Label(1.0F)), + Map.entry(new DataSetEntry(List.of(2.0F, 8.0F)), new Label(1.0F)), + Map.entry(new DataSetEntry(List.of(6.0F, 8.0F)), new Label(-1.0F)), + Map.entry(new DataSetEntry(List.of(6.0F, 9.0F)), new Label(-1.0F)), + Map.entry(new DataSetEntry(List.of(3.0F, 5.0F)), new Label(-1.0F)), + Map.entry(new DataSetEntry(List.of(3.0F, 6.0F)), new Label(-1.0F)), + Map.entry(new DataSetEntry(List.of(3.0F, 8.0F)), new Label(1.0F)), + Map.entry(new DataSetEntry(List.of(3.0F, 9.0F)), new Label(1.0F)), + Map.entry(new DataSetEntry(List.of(5.0F, 7.0F)), new Label(-1.0F)), + Map.entry(new DataSetEntry(List.of(5.0F, 8.0F)), new Label(-1.0F)), + Map.entry(new DataSetEntry(List.of(5.0F, 10.0F)), new Label(1.0F)), + Map.entry(new DataSetEntry(List.of(5.0F, 11.0F)), new Label(1.0F)), + Map.entry(new DataSetEntry(List.of(4.0F, 6.0F)), new Label(-1.0F)), + Map.entry(new DataSetEntry(List.of(4.0F, 7.0F)), new Label(-1.0F)), + Map.entry(new DataSetEntry(List.of(4.0F, 9.0F)), new Label(1.0F)), + Map.entry(new DataSetEntry(List.of(4.0F, 10.0F)), new Label(1.0F)) + )); + + List syns = new ArrayList<>(); + syns.add(new Synapse(new Input(0), new Weight())); + syns.add(new Synapse(new Input(0), new Weight())); + + Bias bias = new Bias(new Weight()); + + Neuron n = new SimplePerceptron(syns, bias, new Linear()); + GradientDescentTraining st = new GradientDescentTraining(); + st.train(n, 0.0003F, dataSet); + } + +} diff --git a/src/main/java/com/naaturel/ANN/domain/abstraction/ActivationFunction.java b/src/main/java/com/naaturel/ANN/domain/abstraction/ActivationFunction.java new file mode 100644 index 0000000..856f95c --- /dev/null +++ b/src/main/java/com/naaturel/ANN/domain/abstraction/ActivationFunction.java @@ -0,0 +1,7 @@ +package com.naaturel.ANN.domain.abstraction; + +public interface ActivationFunction { + + float accept(Neuron n); + +} diff --git a/src/main/java/com/naaturel/ANN/domain/abstraction/Neuron.java b/src/main/java/com/naaturel/ANN/domain/abstraction/Neuron.java new file mode 100644 index 0000000..dd74a52 --- /dev/null +++ b/src/main/java/com/naaturel/ANN/domain/abstraction/Neuron.java @@ -0,0 +1,55 @@ +package com.naaturel.ANN.domain.abstraction; +import com.naaturel.ANN.domain.model.neuron.Bias; +import com.naaturel.ANN.domain.model.neuron.Input; +import com.naaturel.ANN.domain.model.neuron.Synapse; +import com.naaturel.ANN.domain.model.neuron.Weight; + +import java.util.ArrayList; +import java.util.List; + +public abstract class Neuron { + + protected List synapses; + protected Bias bias; + protected ActivationFunction activationFunction; + + public Neuron(List synapses, Bias bias, ActivationFunction func){ + this.synapses = synapses; + this.bias = bias; + this.activationFunction = func; + } + + public abstract float predict(); + public abstract float calculateWeightedSum(); + + public int getSynCount(){ + return this.synapses.size(); + } + + public void setInput(int index, Input input){ + Synapse syn = this.synapses.get(index); + syn.setInput(input.getValue()); + } + + public Bias getBias(){ + return this.bias; + } + + public void updateBias(Weight weight) { + this.bias.setWeight(weight.getValue()); + } + + public Synapse getSynapse(int index){ + return this.synapses.get(index); + } + + public List getSynapses() { + return new ArrayList<>(this.synapses); + } + + public void setWeight(int index, Weight weight){ + Synapse syn = this.synapses.get(index); + syn.setWeight(weight.getValue()); + } + +} diff --git a/src/main/java/com/naaturel/ANN/domain/abstraction/NeuronTrainer.java b/src/main/java/com/naaturel/ANN/domain/abstraction/NeuronTrainer.java new file mode 100644 index 0000000..7127ba0 --- /dev/null +++ b/src/main/java/com/naaturel/ANN/domain/abstraction/NeuronTrainer.java @@ -0,0 +1,13 @@ +package com.naaturel.ANN.domain.abstraction; + +public abstract class NeuronTrainer { + + private Trainable trainable; + + public NeuronTrainer(Trainable trainable){ + this.trainable = trainable; + } + + public abstract void train(); + +} diff --git a/src/main/java/com/naaturel/ANN/domain/abstraction/Trainable.java b/src/main/java/com/naaturel/ANN/domain/abstraction/Trainable.java new file mode 100644 index 0000000..78827f4 --- /dev/null +++ b/src/main/java/com/naaturel/ANN/domain/abstraction/Trainable.java @@ -0,0 +1,7 @@ +package com.naaturel.ANN.domain.abstraction; + +public interface Trainable { + + + +} diff --git a/src/main/java/com/naaturel/ANN/domain/model/dataset/DataSet.java b/src/main/java/com/naaturel/ANN/domain/model/dataset/DataSet.java new file mode 100644 index 0000000..e66e806 --- /dev/null +++ b/src/main/java/com/naaturel/ANN/domain/model/dataset/DataSet.java @@ -0,0 +1,30 @@ +package com.naaturel.ANN.domain.model.dataset; + +import java.util.*; + +public class DataSet implements Iterable{ + + private Map data; + + public DataSet(){ + this(new HashMap<>()); + } + + public DataSet(Map data){ + this.data = data; + } + + public List getData(){ + return new ArrayList<>(this.data.keySet()); + } + + public Label getLabel(DataSetEntry entry){ + return this.data.get(entry); + } + + + @Override + public Iterator iterator() { + return this.data.keySet().iterator(); + } +} diff --git a/src/main/java/com/naaturel/ANN/domain/model/dataset/DataSetEntry.java b/src/main/java/com/naaturel/ANN/domain/model/dataset/DataSetEntry.java new file mode 100644 index 0000000..b2f667d --- /dev/null +++ b/src/main/java/com/naaturel/ANN/domain/model/dataset/DataSetEntry.java @@ -0,0 +1,40 @@ +package com.naaturel.ANN.domain.model.dataset; + +import java.util.*; + +public class DataSetEntry implements Iterable { + + private List data; + + public DataSetEntry(List data){ + this.data = data; + } + + public List getData() { + return new ArrayList<>(data); + } + + + @Override + public int hashCode() { + return Objects.hash(this.data); + } + + @Override + public boolean equals(Object obj) { + if (this == obj) return true; + if (!(obj instanceof DataSetEntry dataSetEntry)) return false; + return Objects.equals(this.data, dataSetEntry.data); + } + + @Override + public Iterator iterator() { + return this.data.iterator(); + } + + + @Override + public String toString() { + return Arrays.toString(this.data.toArray()); + } +} diff --git a/src/main/java/com/naaturel/ANN/domain/model/dataset/Label.java b/src/main/java/com/naaturel/ANN/domain/model/dataset/Label.java new file mode 100644 index 0000000..4f1849e --- /dev/null +++ b/src/main/java/com/naaturel/ANN/domain/model/dataset/Label.java @@ -0,0 +1,15 @@ +package com.naaturel.ANN.domain.model.dataset; + +public class Label { + + private float value; + + public Label(float value){ + this.value = value; + } + + + public float getValue() { + return value; + } +} diff --git a/src/main/java/com/naaturel/ANN/domain/model/neuron/Bias.java b/src/main/java/com/naaturel/ANN/domain/model/neuron/Bias.java new file mode 100644 index 0000000..1ce460e --- /dev/null +++ b/src/main/java/com/naaturel/ANN/domain/model/neuron/Bias.java @@ -0,0 +1,8 @@ +package com.naaturel.ANN.domain.model.neuron; + +public class Bias extends Synapse { + + public Bias(Weight weight) { + super(new Input(1), weight); + } +} diff --git a/src/main/java/com/naaturel/ANN/domain/model/neuron/Input.java b/src/main/java/com/naaturel/ANN/domain/model/neuron/Input.java new file mode 100644 index 0000000..1315231 --- /dev/null +++ b/src/main/java/com/naaturel/ANN/domain/model/neuron/Input.java @@ -0,0 +1,20 @@ +package com.naaturel.ANN.domain.model.neuron; + +public class Input { + + private float value; + + public Input(float value){ + this.value = value; + } + + public void setValue(float value){ + this.value = value; + } + + public float getValue(){ + return this.value; + } + + +} diff --git a/src/main/java/com/naaturel/ANN/domain/model/neuron/Synapse.java b/src/main/java/com/naaturel/ANN/domain/model/neuron/Synapse.java new file mode 100644 index 0000000..3900de9 --- /dev/null +++ b/src/main/java/com/naaturel/ANN/domain/model/neuron/Synapse.java @@ -0,0 +1,30 @@ +package com.naaturel.ANN.domain.model.neuron; + +public class Synapse { + + private Input input; + private Weight weight; + + public Synapse(Input input, Weight weight){ + this.input = input; + this.weight = weight; + } + + public float getInput(){ + return this.input.getValue(); + } + + public void setInput(float value){ + this.input.setValue(value); + } + + public float getWeight() { + return weight.getValue(); + } + + public void setWeight(float value){ + this.weight.setValue(value); + } + + +} diff --git a/src/main/java/com/naaturel/ANN/domain/model/neuron/Weight.java b/src/main/java/com/naaturel/ANN/domain/model/neuron/Weight.java new file mode 100644 index 0000000..515b238 --- /dev/null +++ b/src/main/java/com/naaturel/ANN/domain/model/neuron/Weight.java @@ -0,0 +1,25 @@ +package com.naaturel.ANN.domain.model.neuron; + +import java.util.Random; + +public class Weight { + + private float value; + + public Weight(){ + this(new Random().nextFloat() * 2 - 1); + } + + public Weight(float value){ + this.value = value; + } + + public void setValue(float value){ + this.value = value; + } + + public float getValue(){ + return this.value; + } + +} diff --git a/src/main/java/com/naaturel/ANN/implementation/activationFunction/Heaviside.java b/src/main/java/com/naaturel/ANN/implementation/activationFunction/Heaviside.java new file mode 100644 index 0000000..aae8b52 --- /dev/null +++ b/src/main/java/com/naaturel/ANN/implementation/activationFunction/Heaviside.java @@ -0,0 +1,17 @@ +package com.naaturel.ANN.implementation.activationFunction; + +import com.naaturel.ANN.domain.abstraction.ActivationFunction; +import com.naaturel.ANN.domain.abstraction.Neuron; + +public class Heaviside implements ActivationFunction { + + public Heaviside(){ + + } + + @Override + public float accept(Neuron n) { + float weightedSum = n.calculateWeightedSum(); + return weightedSum <= 0 ? 0:1; + } +} diff --git a/src/main/java/com/naaturel/ANN/implementation/activationFunction/Linear.java b/src/main/java/com/naaturel/ANN/implementation/activationFunction/Linear.java new file mode 100644 index 0000000..c280dac --- /dev/null +++ b/src/main/java/com/naaturel/ANN/implementation/activationFunction/Linear.java @@ -0,0 +1,13 @@ +package com.naaturel.ANN.implementation.activationFunction; + +import com.naaturel.ANN.domain.abstraction.ActivationFunction; +import com.naaturel.ANN.domain.abstraction.Neuron; + +public class Linear implements ActivationFunction { + + @Override + public float accept(Neuron n) { + return n.calculateWeightedSum(); + } + +} diff --git a/src/main/java/com/naaturel/ANN/implementation/neuron/SimplePerceptron.java b/src/main/java/com/naaturel/ANN/implementation/neuron/SimplePerceptron.java new file mode 100644 index 0000000..bc08448 --- /dev/null +++ b/src/main/java/com/naaturel/ANN/implementation/neuron/SimplePerceptron.java @@ -0,0 +1,32 @@ +package com.naaturel.ANN.implementation.neuron; + +import com.naaturel.ANN.domain.abstraction.ActivationFunction; +import com.naaturel.ANN.domain.abstraction.Neuron; +import com.naaturel.ANN.domain.abstraction.Trainable; +import com.naaturel.ANN.domain.model.neuron.Bias; +import com.naaturel.ANN.domain.model.neuron.Synapse; + +import java.util.List; + +public class SimplePerceptron extends Neuron implements Trainable { + + public SimplePerceptron(List synapses, Bias b, ActivationFunction func) { + super(synapses, b, func); + } + + @Override + public float predict() { + return activationFunction.accept(this); + } + + @Override + public float calculateWeightedSum() { + float res = 0; + for(Synapse syn : super.synapses){ + res += syn.getWeight() * syn.getInput(); + } + + return res; + } + +} diff --git a/src/main/java/com/naaturel/ANN/implementation/training/AdalineTraining.java b/src/main/java/com/naaturel/ANN/implementation/training/AdalineTraining.java new file mode 100644 index 0000000..1a58e99 --- /dev/null +++ b/src/main/java/com/naaturel/ANN/implementation/training/AdalineTraining.java @@ -0,0 +1,4 @@ +package com.naaturel.ANN.implementation.training; + +public class AdalineTraining { +} diff --git a/src/main/java/com/naaturel/ANN/implementation/training/GradientDescentTraining.java b/src/main/java/com/naaturel/ANN/implementation/training/GradientDescentTraining.java new file mode 100644 index 0000000..d99d704 --- /dev/null +++ b/src/main/java/com/naaturel/ANN/implementation/training/GradientDescentTraining.java @@ -0,0 +1,99 @@ +package com.naaturel.ANN.implementation.training; + +import com.naaturel.ANN.domain.abstraction.Neuron; +import com.naaturel.ANN.domain.model.dataset.DataSet; +import com.naaturel.ANN.domain.model.dataset.DataSetEntry; +import com.naaturel.ANN.domain.model.neuron.Bias; +import com.naaturel.ANN.domain.model.neuron.Input; +import com.naaturel.ANN.domain.model.neuron.Synapse; +import com.naaturel.ANN.domain.model.neuron.Weight; + +import java.util.ArrayList; +import java.util.List; + +public class GradientDescentTraining { + + public GradientDescentTraining(){ + + } + + public void train(Neuron n, float learningRate, DataSet dataSet) { + int epoch = 1; + int maxEpoch = 10000; + float errorThreshold = 0.125F; + float currentError; + + do { + if(epoch > maxEpoch) break; + + float biasCorrector = 0; + currentError = 0; + List correctorTerms = this.initCorrectorTerms(n.getSynCount()); + + for(DataSetEntry entry : dataSet) { + this.updateInputs(n, entry); + float prediction = n.predict(); + float expectation = dataSet.getLabel(entry).getValue(); + float delta = this.calculateDelta(expectation, prediction); + float loss = this.calculateLoss(delta); + + currentError += loss; + Bias b = n.getBias(); + biasCorrector += this.calculateWeightCorrection(learningRate, b.getInput(), delta); + + for(int i = 0; i < correctorTerms.size(); i++){ + Synapse syn = n.getSynapse(i); + float c = correctorTerms.get(i); + c += this.calculateWeightCorrection(learningRate, syn.getInput(), delta); + correctorTerms.set(i, c); + } + System.out.printf("Epoch : %d ", epoch); + System.out.printf("predicted : %.2f, ", prediction); + System.out.printf("expected : %.2f, ", expectation); + System.out.printf("delta : %.2f, ", delta); + System.out.printf("loss : %.2f\n", loss); + + } + System.out.printf("[Total error : %.2f]\n", currentError); + n.updateBias(new Weight(biasCorrector)); + + for(int i = 0; i < correctorTerms.size(); i++){ + Synapse syn = n.getSynapse(i); + float c = correctorTerms.get(i); + syn.setWeight(syn.getWeight() + c); + } + + epoch++; + } while(currentError > errorThreshold); + + } + + private List initCorrectorTerms(int number){ + List res = new ArrayList<>(); + for(int i = 0; i < number; i++){ + res.add(0F); + } + return res; + } + + private void updateInputs(Neuron n, DataSetEntry entry){ + int index = 0; + for(float value : entry){ + n.setInput(index, new Input(value)); + index++; + } + } + + private float calculateDelta(float expected, float predicted){ + return expected - predicted; + } + + private float calculateLoss(float delta){ + return ((float) Math.pow(delta, 2))/2; + } + + private float calculateWeightCorrection(float lr, float value, float delta){ + return lr * value * delta; + } + +} diff --git a/src/main/java/com/naaturel/ANN/implementation/training/SimpleTraining.java b/src/main/java/com/naaturel/ANN/implementation/training/SimpleTraining.java new file mode 100644 index 0000000..64ced34 --- /dev/null +++ b/src/main/java/com/naaturel/ANN/implementation/training/SimpleTraining.java @@ -0,0 +1,68 @@ +package com.naaturel.ANN.implementation.training; + +import com.naaturel.ANN.domain.abstraction.Neuron; +import com.naaturel.ANN.domain.model.dataset.DataSet; +import com.naaturel.ANN.domain.model.dataset.DataSetEntry; +import com.naaturel.ANN.domain.model.neuron.Input; +import com.naaturel.ANN.domain.model.neuron.Synapse; +import com.naaturel.ANN.domain.model.neuron.Weight; + +public class SimpleTraining { + + public SimpleTraining() { + + } + + public void train(Neuron n, float learningRate, DataSet dataSet) { + int epoch = 1; + int errorCount; + + do { + errorCount = 0; + System.out.printf("Epoch : %d\n", epoch); + for(DataSetEntry entry : dataSet) { + this.updateInputs(n, entry); + float prediction = n.predict(); + float expectation = dataSet.getLabel(entry).getValue(); + float delta = this.calculateDelta(expectation, prediction); + float loss = this.calculateLoss(delta); + if(delta > 1e-6f) { + this.updateWeights(n, learningRate, delta); + errorCount += 1; + } + System.out.printf("predicted : %.2f, ", prediction); + System.out.printf("expected : %.2f, ", expectation); + System.out.printf("delta : %.2f\n", this.calculateDelta(expectation, prediction)); + } + System.out.print("====================================\n"); + epoch++; + } while (errorCount != 0); + } + + private void updateInputs(Neuron n, DataSetEntry entry){ + int index = 0; + for(float value : entry){ + n.setInput(index, new Input(value)); + index++; + } + } + + private void updateWeights(Neuron n, float rate, float delta){ + + Weight biasCorrection = new Weight(n.getBias().getWeight() + (rate * delta * n.getBias().getInput())); + n.updateBias(biasCorrection); + + for(Synapse syn : n.getSynapses()){ + syn.setWeight(syn.getWeight() + (rate * delta * syn.getInput())); + } + } + + private float calculateDelta(float expected, float predicted){ + return expected - predicted; + } + + private float calculateLoss(float delta){ + return Math.abs(delta); + } + +}