Statistical classification is the problem of identifying the sub-population to which new observations belong, where the identity of the sub-population is unknown, on the basis of a training set of data containing observations whose sub-population is known. Therefore these classifications will show a ...

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13 views

how can we calculate the mean return time from state i to state j of markov chain in R?

I have calculated the mean state time from state i to i which is the reciprocal of stationary distribution E=1/pi where pi is stationary distribution in R can use the function ...
-1
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0answers
15 views

autoclassification in R [on hold]

Can you tell me, is there in R the possibility to choose the method that gives the most accurate classification well, for example ...
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0answers
11 views

weak classifier with weak features

I have a set of weak features, and I am looking to create a weak classifier based on them. I am only trying to be right in ~60% of the case (that's enough for my problem). Is there a literature on ...
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1answer
50 views

Discretizing Continuous Outcomes: good examples?

My continuous dependent variable has a lot of error in it. Hence, I was thinking of discretizing it, to reduce the error for my modeling effort. But firstly, the main focus of my modeling effort are ...
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0answers
5 views

svm audio classification [on hold]

I am working in project for classifing a human voice with SVM and it is based on the MFCC coefficient. I have the program in matlab to calculate MFCC, it gives 12 vector of MFCC. and I have the ...
2
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0answers
17 views

Two-classes LDA on third class

I am trying to implement a $N$ classes classification with several 2-classes LDAs. I actually am using LDA as a projection method instead of classification, so it might be more a factor analysis. If ...
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0answers
9 views

How to classify group of events (or actions) from an event log

Given data that contains events carried by group members (e.g., in the format of 'group_id, member_id, event_id, timestamp'), and label for such history data mapping a sequence of group interaction ...
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1answer
34 views

What should be validation strategy?

I am building CTR(https://en.wikipedia.org/wiki/Click-through_rate) Click prediction model with different (61) variables.Dependent variable is weather 0/1( click).I have build logistic regression ...
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25 views

Can a model recognize the interactions between variables?

I have a data set similar to the following one, ...
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7 views

converting feature from string to categorical reduces classification accuracy

I am working on San Francisco crime classification problem from kaggle. https://www.kaggle.com/c/sf-crime during the work I encountered something unexpected. I applied scikit learn's random forest ...
3
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1answer
44 views

Bayesian treatment of outliers

In a supervised learning problem, I have a training dataset $D$ comprised of samples $x$ and their corresponding labels $\omega$. From this data, I attempt to learn the true distributions ...
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1answer
7 views

Handling missing/rare levels in predictor in data samples

Let us assume we have a dataset with one catigorical variable, which is represented in R as a factor. I am performing crossvalidation to assess models, for which I need to perform stratified sampling ...
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0answers
29 views

Solve KNN classification using both categorical and quantitative variables in r [on hold]

Im new in this field, I am trying to classify a data set (what influence the alcohol consumption of young people, made of 32 variables like age, family situation, absences at school, etc.) using r. I ...
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9 views

Classification of overlapping hetegenerous cell nuclei

We are two people doing a image analysis project on segmentation of cell nuclei. Our data set consist of about 300-400 cell nuclei, from 10-15 images containing different cell types. Our main problem ...
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1answer
23 views

The meaning of Classification Accuracy

I'm working on San Francisco Crime dataset, and only get about 20% classification accuracy. I used Random Forest Method. So how I can Interpret the result? I did EDA firstly, but how can I use EDA to ...
3
votes
2answers
49 views

Completely different results after each cross validation

I'm running some classification algorithms in MATLAB and validating them with a 10-fold cross validation. The problem is that every time I execute the cross validation, it gives a very different ...
0
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1answer
17 views

Large number of positive labels in classifier when actual population has few

I have been tasked to help with a sort of classifier. In the make up of the problem the set we want to identify as "Positive" is know to be very very small. However the training set I have been given ...
1
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1answer
27 views

deep learning in mobile apps [closed]

Can deep learning be applied in mobile apps, and if possible how? Is it possible ? to deep learning needs more computational cost? how can we minimize the computational cost for deep learning on ...
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0answers
14 views

Classification Trees

I'm having trouble figuring out how to read classification trees. I've attached an example of a classification tree that predicts whether or not a home is high or low value. Could someone explain ...
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0answers
3 views

How does Weka chiSquaredAttributeEval generates single attribute selection list while Chi Square itself is class based?

I have implemented my own Chi-Square ranker in C# however the example i found on the internet shows that Chi-Square ranks the each attribute within its class However Weka generates attributes as a ...
2
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0answers
29 views

Probability distribution over classes as labels in classification task

Classical classification problem has next formulation. Given a set of $n$ attributes, a set of $k$ classes and a set of labelled training instances: $(i_i, l_j),...,(i_j, l_j)$, where $ i = (v_1, ...
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0answers
17 views

caret for hierarchical classification

I am wondering if there are algorithms in the awesome caret package that deal with hierarchical classification tasks? That is, assume each item can be of class A or ...
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1answer
21 views

Why is the log taken in the formula for weight of evidence?

Why is the logarithm used when calculating the weight of evidence (WOE)? For example, let bin i ($B_i$) have, 15% good 30% bad So good/bad = 0.5. Namely for each bad item there are 0.5 good in ...
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0answers
26 views

Understanding LDA inference

It is said that the key inferential problem that needs to be solved to use LDA (latent dirichlet allocation) is that of computing the posterior distribution $p(\theta,z | w, \alpha ,\beta)$. I know ...
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0answers
3 views

improving efficiency of decision tree C50

Could have some idea how to improve efficiency of decision tree ? I am using C50 package. The only parameter that I may set is number of trials. How to set this parameter ? What about whole hints ...
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2answers
44 views

One-vs-many/One-vs-all - what value to use as probability?

I have constructed SVMs to do a one-vs-many approach to classification. Let's say I have 3 classes and I train 3 SVMs in a one-vs-many format. This gives me 3 SVMs each trained positively on one of a ...
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1answer
24 views

Feature selection step before decision tree?

I want to use rpart (a R package) to build a decision tree model. The data is a high-dimensional expression matrix, with ~50,000 predictors and ~500 samples. The response is a categorical variable. ...
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0answers
14 views

What is unbalanced data in libsvm?

My full data set (inclusive of both trng & test) has about 350 rows. They are of 3 classes (1,2,3), 1 has about 70, 2 has 125, 3 has 150. The above distribution across the labels is playing a ...
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0answers
13 views

Finding a number that considers %worse outcomes and %better outcomes

I have a baseline algorithm and lots of test algorithms. The baseline algorithm's performance is compared to every other algorithm. What I'm left with is a table like so: ...
0
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0answers
13 views

Part-of-speech tags as Document Term Matrix

For my thesis I need to apply a part-of-speech tagging for sentiment classification in R. I have a dataset consisting of ~800 sentences which were tagged by the ...
0
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1answer
17 views

How to use Cross_validation output of svm-train?

I am getting very poor values with a certain data set I have. I tried to use the -v option of svm-train but later realized that this does not produce any model file for prediction. So what is the ...
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0answers
17 views

Classification on sequential data

Context: I am working on a classification project where I recommend items to customers based on their past purchase history. Question: How will "time leakage" affect training? Example: Let's say ...
1
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1answer
29 views

Machine learning step order question

I have been working on this project for over a year now and I believe i finally have things figured out. Mainly i'm looking for any suggestions or things i'm doing wrong with my process, but i also ...
1
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0answers
11 views

What can I infer about my problem domain/input data from the hyperparameters producing the optimum network configuration?

I am new to neural networks and am trying to solve a binary classification problem with a neural network. I tried network configurations with 1 to 6 hidden layers, and 1-50 neurons per layer. The ...
1
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0answers
5 views

Training a binary LSTM classifier with few true positives

I'm trying to solve a multilabel classification problem with n-binary LSTM classifiers. I have 17 classes in total, where multiple classes may be true for each example (e.g. news articles with ...
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0answers
50 views

Problem Training an LSTM network in Lasagne for simple task (determining parity of bit sequence)

I have been trying to gain some familiarity with the Lasagne libraries for machine learning, specifically LSTMs so I set up the following toy problem to determine the parity of a sequence of bits ...
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0answers
10 views

K-NN Binary classification with boolean features

inexperienced forum user and ML 'user'. I'm trying to shed some light on some data. The feature vector is all booleans (isMale, isAmerican, hasMac etc..) and it is a binary classification problem. ...
0
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1answer
25 views

KNN classifier + cross validation

how can I find the mean and standard deviation of error rate or accuracy of a k- fold cross validation performing K-nearest-neighbour classification model for each fold?
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0answers
15 views

Naive Bayes + k- fold Cross Validation

How can I find the mean and standard deviation of the accuracy of k-fold cross validation when the classifier method is Naive Bayes?
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0answers
73 views

Generate code for sklearn's GradientBoostingClassifier

I want to generate code (Python for now, but ultimately C) from a trained gradient boosted classifier (from sklearn). As far as I understand it, the model takes an initial predictor, and then adds ...
0
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0answers
20 views

Classifiers which only answer when they are confident?

It is often true that a classifier (or regression) can give some kind of confidence in its answers, e.g. through bootstrapping. However, this is often viewed as an afterthought: "here is the answer, ...
0
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2answers
27 views

10 class problems with 324 features - am I recognition class based on multiple features, class based on the pattern of one feature?

I am trying to balance 324 features for a 10 class problems, but it just seem humanly impossible, The problem i am studying consist of recognizing character , each observation consist of 324 ...
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0answers
21 views

How to detect the events using NLP and Machine learning?

I have text describing about events such as birth , new job , wedding , death etc .. or no event . How do i detect these events ? My approach is to form set of words and search them in text ...
0
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0answers
9 views

Constraint on maximal margin classifier

When I learned the maximal margin classifier, I saw the following definitions: \begin{align} &{\rm maximize}_{\beta_0...\beta_p}M \tag{1} \\ &\sum_{j=1}^{p}{\beta_j}^2 = 1 \tag{2} \\ ...
0
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0answers
8 views

Using priors, weights or costs for mitigating class imbalance?

A plethora of Matlab classifiers (e.g. tree-based or svm) allow to set priors, costs or weights for the data points. This can help dealing with imbalanced data. Unfortunately, none does support ...
1
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0answers
12 views

Create a model based on the distribution of data for classification purposes

I have data set which is stored as a matrix where each row is an observation (number of observations listed is 4000 ) and each column the feature extracted from that observation (number of features ...
0
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0answers
21 views

why am i getting bad predictions rates?

I am trying to make a classifier capable of recognizing digits using the naive bayes method. Problem is though that i am getting pretty bad results. I thought the reason would be because of the ...
1
vote
0answers
29 views

What is the efficient preprocessing data in image classification task with CNN?

I am new in deep learning on image classification. I know that Machine learning algorithm are very dependent to data normalization. Usually, if we have a training data set represented with X [N*D] ...
0
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0answers
16 views

How to interpret the the train result?

I using the caret trained my dataset using naive bayesian as method with an repeated 10-fold cross validation. I seem to get a lot of different output, but can't ...
0
votes
1answer
13 views

Classification based on a large number of independent continuous variables

What machine learning algorithm would be the most optimal to use for a classification problem with a small number of classes? In my case, only two. The sample size is also rather small (<100), but ...