Hi all, I know the subject is ugly but I don¹t really know how to call it.
I am newbie with all this machine learning techniques and what I do most of the time is to follow a ³try and error² approach. I now this method has some inconvenients but for now is what I am able to do. I am working with text on a classification problem. My pipeline is: TfidfVectorizer, feature selection with f_classif/Chi and the final classifier(I have tried lot of different classifiers). Unfortunately, the results that I am getting are very poor. The measurement that I am using is the AUC. The best result has been an AUC of 62(I have tried without doing feature selection too). Using same dataset but using R I have obtain an AUC of 0.90. In the process, I am using frequencies obtained with Scikit(I process the frequencies using TfidfVectorizer and later I store the resulting dataset on a csv). No feature selection is used and the classifier is a logistic regression: out.glm.1 <- glm(equat, data=dataset[,c(input, target)], family=binomial(link="logit²)) Is there someone that could tell me how to ³replicate² this with Scikit? And more, someone knows any resource ³easy to follow² where I can understand the underlying implementation on both libraries? In general, I found that Scikit has links to the source of the implementation(I mean, the original papers). On the other hand, I found R documentation very difficult to follow(parameters explanation) and there aren¹t too much details on the implementation. Thanks in advance. ________________________________ Este mensaje y sus adjuntos se dirigen exclusivamente a su destinatario, puede contener información privilegiada o confidencial y es para uso exclusivo de la persona o entidad de destino. Si no es usted. el destinatario indicado, queda notificado de que la lectura, utilización, divulgación y/o copia sin autorización puede estar prohibida en virtud de la legislación vigente. Si ha recibido este mensaje por error, le rogamos que nos lo comunique inmediatamente por esta misma vía y proceda a su destrucción. The information contained in this transmission is privileged and confidential information intended only for the use of the individual or entity named above. If the reader of this message is not the intended recipient, you are hereby notified that any dissemination, distribution or copying of this communication is strictly prohibited. If you have received this transmission in error, do not read it. Please immediately reply to the sender that you have received this communication in error and then delete it. Esta mensagem e seus anexos se dirigem exclusivamente ao seu destinatário, pode conter informação privilegiada ou confidencial e é para uso exclusivo da pessoa ou entidade de destino. Se não é vossa senhoria o destinatário indicado, fica notificado de que a leitura, utilização, divulgação e/ou cópia sem autorização pode estar proibida em virtude da legislação vigente. Se recebeu esta mensagem por erro, rogamos-lhe que nos o comunique imediatamente por esta mesma via e proceda a sua destruição ------------------------------------------------------------------------------ Slashdot TV. Videos for Nerds. Stuff that Matters. http://pubads.g.doubleclick.net/gampad/clk?id=160591471&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
