-
Install CNTLM in a folder where you have full rights to run it as administrator.
-
Open
cntlm.ini
and fill it :
Username YOUR_USERNAME
Domain YOUR_DOMAIN
""" | |
Multiclass SVMs (Crammer-Singer formulation). | |
A pure Python re-implementation of: | |
Large-scale Multiclass Support Vector Machine Training via Euclidean Projection onto the Simplex. | |
Mathieu Blondel, Akinori Fujino, and Naonori Ueda. | |
ICPR 2014. | |
http://www.mblondel.org/publications/mblondel-icpr2014.pdf | |
""" |
def smoSimple(dataIn, classLabels, C, tolerance, maxIter): | |
dataMatrix = mat(dataIn) | |
labelMat = mat(classLabels).T | |
m, n = shape(dataMatrix) | |
alphas = mat(zeros((m,1))) | |
bias = 0 | |
iter = 0 | |
while (iter < maxIter): |
public void dumpAndLoadTo(String targetPath) throws IOException, InterruptedException { | |
// I first tried something like this: | |
// neo4j-shell -path outDir -c "DUMP MATCH n RETURN n;" | neo4j-shell -path targetPath -file - | |
// but performance was horrible upon import. | |
// See http://stackoverflow.com/questions/28246416/neo4j-export-import-data . | |
logger.info("Loading to db " + targetPath); | |
GraphDatabaseService dbSrc = getDb(); | |
GraphDatabaseService dbDest = getDb(targetPath); |
Install CNTLM in a folder where you have full rights to run it as administrator.
Open cntlm.ini
and fill it :
Username YOUR_USERNAME
Domain YOUR_DOMAIN
Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.
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