GitHub - jxt1234/Abstract_Learning: A Quick Machine Learning Library

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 75 Commits
build		build
cmake/Modules		cmake/Modules
cpptools		cpptools
data		data
doc		doc
dump		dump
include		include
jni		jni
opencl		opencl
output		output
pieces/lenet/info		pieces/lenet/info
res/cnn		res/cnn
src		src
test		test
third/cJSON		third/cJSON
tools		tools
.gitignore		.gitignore
CMakeLists.txt		CMakeLists.txt
LICENSE		LICENSE
Map-Reduce.xml		Map-Reduce.xml
README.txt		README.txt
UpthreadLabeld.h		UpthreadLabeld.h
a1a		a1a
a1a.model		a1a.model
a1a.predict		a1a.predict
a1a.tra		a1a.tra
bao.txt		bao.txt
bao2.txt		bao2.txt
bao_normal.txt		bao_normal.txt
bao_predict.txt		bao_predict.txt
bao_predict_normal.txt		bao_predict_normal.txt
bitebi.txt		bitebi.txt
cnn_parallel.py		cnn_parallel.py
cnn_single.py		cnn_single.py
createFile.py		createFile.py
data_eco.txt		data_eco.txt
doc.txt		doc.txt
example.cpp		example.cpp
example.py		example.py
example2.py		example2.py
gp_test.cpp		gp_test.cpp
libAbstract_learning.xml		libAbstract_learning.xml
lstm_single.cpp		lstm_single.cpp
mgpfunc.xml		mgpfunc.xml
normalizer.py		normalizer.py
rf_train.py		rf_train.py
splitData.py		splitData.py
struct.txt		struct.txt
tree_model.xml		tree_model.xml
yu_e_bao.txt		yu_e_bao.txt

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适用于PC端、服务器、手机端的机器学习算法库

PC端和服务端安装：
先安装 Renascence
https://github.com/jxt1234/Renascence

用法参考 ./rf_train.py ./cnn_parallel.py ./cnn_single.py


手机端(Android)：
建议用 Renascence 的java API 动态加载与运行，也可以自行编写jni封装。