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 ...
3
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1answer
35 views
prequential evaluation - classification
I perform prequential evaluation like this: start with a training set, classify a number of examples, then add the correctly classified examples in the training set and continue to classifying the ...
2
votes
1answer
47 views
Sample size with respect to prediction in classification and regression
With respect to hypothesis testing, estimating samples sizes is done through
power, and it is intuitive that increasing the same size increases
the precision of estimated effects. But what about ...
0
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0answers
77 views
Understanding Naive and Multivariate Gaussian Classifier
Thank you for checking this question out.
I am trying to understand how to use the multivariate gaussian classifier.
To introduce you better to my problem, I will show how currently I classify data.
...
1
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0answers
9 views
Decision trees partitioning predictors?
In general, decision trees such as CART represent row-wise (or record-wise) partitions of training data. I wonder if there is any recursive method partitioning data in column-wise (predictor-wise) as ...
7
votes
2answers
282 views
Test accuracy higher than training. How to interpret?
A ML newbie here.
I've a dataset containing at most 150 examples (splitted to training & test), with many features (higher than 1000). I need to compare classifiers and feature selection methods ...
0
votes
1answer
38 views
How does SVM prediction work?
As far as I understand, the training phase usually uses the dual optimization formulation where we can implicitly calculate the weight vector which defines the discriminant function.
How about the ...
1
vote
0answers
39 views
Can we use random forest for classification in combination with distance matrix between classes
With a colleague, we are working on a dataset containing ~5000 continuous variables for 120 individuals belonging to 8 classes.
We want to estimate the relative importance of each variable to explain ...
0
votes
2answers
30 views
clustering gene expression data
I have a question about clustering.
I' m managing gene expression microarray data and I would like to cluster them in classes.
I searched around to find the best clustering algorithm for my data, ...
0
votes
1answer
28 views
How to balance classification?
I have a binary classification problem, where my training data is 70% positive labeled and 30% negative labelled. I use a logistic loss and it always classifies examples positive on the test data.
...
0
votes
0answers
26 views
Statistical Significance test for difference in FScore
For a classification task, I have developed two methods and FScore(harmonic mean of precision and recall) of both the classes serves as the performance criteria. How can I check whether the difference ...
-1
votes
2answers
42 views
Accuracy and Statistical Significance [closed]
According to experimental result, One approach has 10% better accuracy over the other.
My supervisor said that this should be coupled with an estimative of the statistical significance of this ...
2
votes
0answers
43 views
Procrustes Analysis of 3d point cloud without defined landmarks
I am working with several hundred 3d point clouds generated using a 3d scanner and would like to be able to compare their shapes using something like a procrustes analysis. Instead of manually ...
1
vote
1answer
50 views
Online logistic regression?
Here is my problem: I am developing an embedded system for some classification task. I am using Logistic Regression as my classifier. Now I train my classifier, and download my model on to my machine. ...
13
votes
1answer
180 views
Random forest assumptions
I am kind of new to random forest so I am still struggling with some basic concepts.
In linear regression, we assume independent observations, constant variance…
What are the basic ...
0
votes
1answer
44 views
Fit of a normal distribution to a one-dimensional dataset in R
I've got a set of (continuous) values from a measurement, where each object should be either positive or negative, and I know that the values of the "negative" objects should be approximately normally ...
1
vote
0answers
24 views
Find exceptional parameters
I have been given an excel document with many rows full of numbers, some rows are marked.
Each row represents a case in the clinic, each column represents a research test parameter.
I need to find, ...
2
votes
0answers
36 views
SVM classifier (with soft-margin) implementation in R, gamma value and quadprog
I'm trying to implement a Support Vector Machine classifier in R and I have to solve the optimization problem using the quadprog R package which solves problems of the form :
$$min_b \frac{1}{2} ...
2
votes
1answer
46 views
Compare classifiers based on AUROC or accuracy?
I have a binary classification problem and I experiment different classifiers on it:
I want to compare the classifiers. which one is a better measure AUC or accuracy? And why?
...
0
votes
0answers
19 views
Classification rate
I have used ordinal logistic regression where the response variable is NPS and the explanatory variables are different questions. I have found a model where all the questions in it are significant. ...
2
votes
1answer
77 views
Recommend classification algorithms to try
I am working on a binary classification problem that is reasonably-sized (100k observations). I extracted 60 numerical features; the classes in the training set are well balanced. There are some ...
1
vote
1answer
29 views
Features selection using F-score for multiclass classification
I'm going to implement a feature selection algorithm, and I plan to use the F-score for because of its simplicity. The problem is that, the F-score is used for binary classification. How can it be ...
0
votes
1answer
48 views
regularized logistic regression and support vector machine
L2 regularized logistic regression differs with L2 regularized support vector machine with their loss function. Are there more deep differences for these two models? I tried several data sets, and ...
0
votes
1answer
55 views
How to evaluate concordance between 2 raters and factors that affect the concordance
I have about 1000 subjects ($id$) and each of them has some baseline variables (demographic variables $X1, X2, X3, Xn$, which can be continuous, factors). Every subject is classified by two raters ...
1
vote
0answers
29 views
Using PCA to merge and grade correlated items
I have a real estates' condos sold dataset with the following fields
DOM: Date on the market
sellPct: Percentage difference between the original and final price.
other fields such as Exposure( ...
0
votes
0answers
22 views
What are some references for works which used synthetic True Negatives for the purpose of training a classifier?
I am searching for previous research papers which used a synthetic True Negative set for training a classifier (preferably a Random Forests one). The synthetic true negative set could have been built ...
0
votes
0answers
44 views
How can one setup a linear support vector machine in excel?
Through the last year I have been working with support vector machines for a binary text classification task. Having used software as R and Rapidminer I have not spend much time on understanding what ...
2
votes
1answer
182 views
Should I expect it to be a chicken or a penguin?
An alien is trying to classify a group of only chickens and penguins into, well, chickens and penguins by analyzing 3 independent boolean features A, B, C.
If the animal (in reality) is a chicken, A ...
0
votes
0answers
21 views
Pegasos algorithm parameters estimation
For learning pourpose I'm testing my own implementation of the Pegasos algorithm and I'm getting a quite high error rate.
My dataset contains 20k examples and I'm using 17,5k of them for the training ...
5
votes
2answers
81 views
Why do categorical predictor variables in regression need to be recoded as multiple predictors?
I'm learning about machine learning using Python's library scikit learn, and in their tutorial here they mentioned about a categorical variable color which can have ...
1
vote
0answers
19 views
Problem with classifier after using SMOTE to balance the data
We've ran into a problem while training a classifier on an unbalanced data set.
The response is binary with 0 indicating 'non defaulter' and 1 indicating 'defaulter' (it's a credit scoring task).
...
0
votes
0answers
41 views
Binary Classification
I have conducted 2 experiments on two parameters, $P1$ and $P2$, and I want to classify the two parameters for each experiment.
Experiment 1
...
1
vote
0answers
37 views
Computing a bootstrap confidence interval for the prediction error with the percentile and the BCa method
I have two related questions regarding the computation of a non-parametric bootstrap confidence interval for the prediction error.
Setting: I have a sample S from a data population P and a learner L, ...
2
votes
1answer
73 views
confidence interval for classification error---binomial assumption vs. bootsrap resampling
I am developing a classifier using a set of N patterns, where N~1000. I am using K-fold cross-validation (with K=5) and computing the probability of classification error p (typical value is p=0.03). ...
2
votes
3answers
192 views
Why is svm not so good as decision tree on the same data?
I am new to machine learning and try to use scikit-learn(sklearn) to deal with a classification problem. Both DecisionTree and SVM can train a classifier for this problem.
I use ...
3
votes
2answers
31 views
Naive Bayes feature probabilities (Do I double count words?)
I'm prototyping my own Naive Bayes bag o' words model, and I had a question about calculating the feature probabilities.
Let's say I've got two classes, I'll just use spam and not-spam since that's ...
1
vote
2answers
60 views
Highly unbalanced test data set and balanced training data in classification
I have a training set with about 3000 positive instances and 3000 negative instances. But my test data set is pretty much un-balanced. The positive set only has 50 instances and negative has 1500 ...
0
votes
0answers
30 views
two component non standard mixture (normal + unknown)
I have some univariate data which might be well modeled as a two component mixture where the first component is normal with unknown mean and variance and the second is some unspecified continuous ...
1
vote
0answers
46 views
Alternative to Shannon's entropy when probabilty equal to zero
I have a serie of objects for whom I know the probability of belonging to 10 classes. This probability can be null (see example below with 4 classes).
...
0
votes
0answers
44 views
trouble in prediction in neural network classifier
I am training a 4-class neural network classifier.
The details of my data are:
featurelength = 280
...
0
votes
0answers
20 views
Relationship between vector dimesion and number of training samples for binary classifer
I have some general questions about binary classifers.
Is there any relationship between sample vector dimesions and number of training samples for classifer?
Is it good or bad to provide samples ...
1
vote
0answers
65 views
k-fold cross validation vs k times hold-out validation
I am facing the evaluation of a genetic programming algorithm. I am using the Proben1 cancer1 dataset to evaluate the models created by this algorithm. This dataset contains 699 samples, which is ...
0
votes
1answer
37 views
Using F1_score to measure cluster validity
I have clustered over 4000 textual files, and now I want to check and evaluate clusters. I want to use F-measure (a mix of recall and precision).
The formal definition of F1_score is:
$$
...
0
votes
1answer
17 views
in nonlinear binary classification problems, which is the optimal dimension for make it lineary separable?
My question pertains to linear separability with hyperplanes in a support vector machine.
Is posible to determinate the optimal dimension in which i have to transform a training data set for make it ...
-1
votes
0answers
76 views
Any idea or suggestion for my project data mining?
I am doing my job in the field of classification and data mining, Here is my issue:
Sorry for my poor english.
Context:
About 2 million invoices need to be classified, all these invoices are in ...
-1
votes
0answers
23 views
kernels distances gram matrix classification
Could you please explain some thing about kernels? As I understand it is technique to map the feature space into a high dimensional feature space where we could separate two classes by a linear ...
0
votes
0answers
18 views
Obtaining final classification score using AdaBoost predict function
If I understand correctly, predict.ada() returns an $n$ by 2 matrix of class probabilities for each classifier used in $n$ iterations. How can I obtain the final classification on scale of [0,1] for ...
0
votes
0answers
12 views
Which features to extract for classifying segmented zones of an image into two classes “handwritten text” and “graphics”
I have some chemical document images segmented into different zones, some zones represents "handwritten text" and others represent "graphics". I want to classify this zones into two classes, one for ...
1
vote
1answer
59 views
What method should I use to identify which variables differentiate between objects of two different classes?
To illustrate the problem posed by the question: Consider the problem of differentiating between consumers who belong to two different segments. I could use a naive or a sophisticated approach as ...
1
vote
0answers
56 views
Are the angles between iid training data and the classifier learned from them independent?
Suppose I have a training set $\mathcal{T}^N = \{(x_i , y_i) \in \mathbb{R}^{d} \times \{0,1\}\}$, where the data are i.i.d draws from some distribution.
Now I learn a classifier $\hat{h}$ from these ...
0
votes
0answers
14 views
Parzen Estimation used in Classification
How would I use a Parzen window estimate to classify an arbitrary test point x using 3 dimensional data from three categories.
