Methods and principles of building "computer systems that automatically improve with experience."

learn more… | top users | synonyms

0
votes
0answers
12 views

How to handle large .csv file in R? [migrated]

I have a large(>100,000) single column floating point time-series data. I want to find structural changes within the data with respect to time( in my case index). In-order to do that, I am using R ...
1
vote
0answers
35 views

SVM versus Bayesian regression example(s)?

I am trying to track down examples where some basic problems have been tackled via both classical Machine Learning algorithms and more formal statistical methods. In particular, I'm interested in ...
-1
votes
0answers
47 views

Sales Forecasting using Support Vector Machine

I have sales data for last three years 2011-2013. I want to use Support Vector Machine technique in R to do the predictions. I just wanted to know that the approach that I am using is correct or not? ...
0
votes
0answers
29 views

Hidden Markov Models relationship

I have a question regarding a small investigation that I have been conducting into the relationship between the length of observation sequence, T, on which two decoders (BCJR and classic Viterbi) ...
0
votes
0answers
43 views

The best way to solve particular classification problem?

I got training set (time series) of size approximately 2 million precedents {x,y}. Each x is a vector of size 20 and each y is a binary vector of size 10 like {1,0,0,1,1,0,1,1,1,0}. For a new input x ...
1
vote
0answers
18 views

How do you deal with different distance based features?

If I have a model where the set of features where a cosign distance measure makes sense for some of the features, and a Euclidean distance measure makes sense for the others for example using a BOW ...
0
votes
0answers
10 views

Hyper-parameters for pretrain and fine-tuning

When doing deep learning, in particular dnn, it's shown that pre-train each layer in a unsupervised fashion, then fine-tune the weights using the labeled data in a supervised fashion. My problem is, ...
0
votes
0answers
22 views

Examine SVM result by plotting histogram of decision values of training samples

I'm working for object detection(computer vision) and have some problems in SVM training. My training configuration is as below. Balanced training set (positive 3998/ negative 3998) The dimension of ...
0
votes
0answers
22 views

Choosing fold size for highly Imbalanced dataset + nested CV + svm

I am trying to classify a dataset with ~1000 points. 90/10 is the class ratio - super imbalanced. Here are the following steps I did: Use 20 relevant features from previous knowledge Remove highly ...
1
vote
3answers
151 views

What are the most popular artificial neural network algorithms for recognising the content of images?

What are the most used/popular artificial neural network algorithms for recognising the content of images in general? E.g. If the picture is of a person, dog, cat or a car. If the picture is a ...
0
votes
1answer
29 views

Whats going wrong in Implementation of this gaussian bernoulli RBM?

I have a problem in finding negdata value. In particular multiplying with sigma. Could someone help in representing this equation vishid*sigma*poshidstates + visbias in matlab. ...
0
votes
1answer
53 views

Classification using correlation

Given two correlation matrix (each $p \times p$), where each belongs to a different group, is it possible to classify a new sample into one of the group (based on the correlation matrix only)? What ...
2
votes
2answers
85 views

How does random Forest work for regression?

I am an absolute beginner in field of machine learning, I started doing titanic assignment in Kaggle and found(read some where) Random Forest is the best fit. I started reading about random forest and ...
0
votes
1answer
75 views

High Standard Deviation for Leave one out cross-validation?

I am using the leave one out cross-validation technique to evaluate my model. If the prediction on the test sample is right the output is 1 otherwise 0. So I have a array of N samples with 0's and 1's ...
0
votes
0answers
34 views

different feature types for classification

There has a data set with several features. One feature is of the type of continuous numerical values; another feature is of the type of categorical values, such as A, B and C. If I want to build a ...
0
votes
1answer
25 views

Is my understanding of how to calculate the reachability distance in local outlier factor correct?

Reading lof implementation at : http://www.cse.ust.hk/~leichen/courses/msc-it5210/lectures/LOF_Example.pdf the local reachability distance is given as : I don't fully understand this equation as ...
0
votes
1answer
16 views

How to use a set attributes of an entity at different time snaps to make predictive analysis?

The problem is to come up with a classifier for any task based on a set of attributes of an entity having different values at different times. For instance think about football players and their match ...
1
vote
0answers
15 views

Applying autoencoders for dimensionality reduction in audio: Why does this create a low-pass effect? [closed]

I've been playing around with framing audio data and training a single-layer autoencoder to find a dimensionality-reduced form (say 128-sample frames to 32-dimension frames). When I test the audio ...
1
vote
2answers
188 views

When to avoid Random Forest?

Random forests are well known to perform fairly well on a variety of tasks and have been referred to as the leatherman of learning methods. Are there any types of problems or specific conditions in ...
1
vote
1answer
46 views

Post hoc selection of important features in random forest?

I want to guarantee a parsimonious random forest (few features used). What are methods to do this? It was suggested to me to get the feature importance after the model was created, and then create a ...
0
votes
0answers
29 views

Validation accuracy larger than training accuracy

I was performing an experiment but got a higher validation accuracy than training accuracy. I've got a 39 mice data and performed leave one out cross-validation. The validation accuracy was 100%. But ...
2
votes
2answers
32 views

Accuracy of random prediction with non equal distribution

Assume that I want to predict the value of a variable that has three different states: a, b, and c. The chance that these variables have the 3 states is not equally distributed. Out of 10 trials, the ...
2
votes
2answers
57 views

Which property of count data make mean-variance dependency?

I have read about the fact that, there is dependency of variance on mean of count data.In most of cases they do variance stabilization transfomration as preprocessing step of data modeling. I wonder, ...
0
votes
1answer
38 views

Multi-class Confusion Matrix to Binary confusion matrix

i know the main concepts of data/text mining but i used them mainly in binary classification problems (just two classes). i am now dealing with a problem with 8 classes and i am atruggling how to ...
0
votes
0answers
22 views

How to deal with a feature relating to what type of expert labelled the data that becomes unavailable at point of classification?

Essentially I have a data set, that has a feature vector, and label indicating whether it is spam or non-spam. To get the labels for this data, 2 distinct types of expert were used each using ...
0
votes
1answer
62 views

why use Supervised vs Unsupervised given the class label?

Hi I have data set with a set of variables and known class labels. I am trying to compare why a supervised approach will work theoretically better compared to a unsupervised approach for ...
1
vote
0answers
68 views

MHT: Pre-Selecting statistical tests without Bias

Summary: The last formula boxed in red (which is a modified log likelihood from logistic regression) is a special non-differentiable loss function that is adapted to contain a Bonferroni correction in ...
0
votes
0answers
22 views

auto-steering using neural networks

I was hoping if anyone could point me in right direction, I want to implement a neural network that could steer an autonomous car, I have implemented basic classification problems before using single ...
2
votes
4answers
96 views

Interpreting conflicting results from Random Forest & Logistic Regression?

I am using SKLearn and Statsmodel in python to build a RF and Logistic Regression, respectively. I have a feature that the RF indicates is important (feature importance of 0.202, closely behind #1 ...
1
vote
1answer
31 views

How should the precision/recall be calculated for classes in datasets with NO true class instances?

I have built a classification model to recognise a class and I have evaluated it on several datasets. The problem is that some of these datasets do not have any true instance of the class in question, ...
0
votes
0answers
4 views

what is the meaning of the Samples in NER?

I would like to know in NER (Named Entity Recognition ) problem , which concept should be considered as samples? each token as a sample? or each sentence ? or each Named Entity should be considered ...
0
votes
0answers
25 views

What is the difference between Contrastive divergence k and persistent contrastive divergence algorithm?

As per my understanding Contrastive divergence k is obtaining v(k) after k steps of gibbs chain. Persistent contrastive divergence is obtaining v(k) independent of v(0). I am quite confused with the ...
0
votes
0answers
29 views

Which statistics to use in order to understand a dataset?

So I have a dataset that I will use to train a bunch of classifiers. I need to do that for my thesis. However I'm not sure which statistics are good to use to better understand the dataset and the ...
0
votes
2answers
77 views

Using decision trees to make a binary decision

I have a button that I can press or not press, a binary target that I would like to be 1 as often as possible, and a bunch of features. I also have a bunch of (feature, button choice, target) data, in ...
2
votes
0answers
60 views

Unbalanced dataset - ROC curve to compare classifiers?

I use the machine learning software WEKA for data mining on biological data. I would describe my dataset as unbalanced: It comprises around 2000 instances, ...
1
vote
3answers
74 views

Is it necessary to scale the target value in addition to scaling features for regression analysis?

I'm building regression models. As a preprocessing step, I scale my feature values to have mean 0 and standard deviation 1. Is it necessary to normalize the target values also?
0
votes
0answers
30 views

What is task-loss function?

I looked into "Multi-Output Learning for Camera Relocalization" research and faced with the following part (2.2 The Direct Regression Approach): Given a set of RGB-D frames with known camera poses ...
0
votes
1answer
58 views

How to determine which variable or combination of the variables are affecting to the predictor variable?

I have one dependent variable name as "win ration" of the deal contested and more than 30 independent variables, all are categorical variable name as role of the customer, geo, region, and 27 ...
3
votes
4answers
633 views

Solving a practical machine learning problem

I am currently doing my Phd in computational biology at Stanford. I get the data I need to answer the questions I am interested in. The data sets are sometimes "large" and these large problems take ...
2
votes
2answers
112 views

Reproduce linear discriminant analysis projection plot

I'm struggling with projection points in linear discriminant analysis (LDA). Many books on multivariate statistical methods illustrate the idea of the LDA with the figure below. The problem ...
1
vote
0answers
36 views

Neural Networks and Picture Recognition

I have spent a bunch of time looking at this series of videos (Neural Network Tutorial), by Ryan Harris: https://www.youtube.com/watch?v=Q_5B3GuWPCc&index=41&list=PL29C61214F2146796 I am ...
2
votes
1answer
25 views

How to isolate impact of event in a product's lifecycle?

I'm trying to figure out how a single event affects sales numbers of a song. For example, see what the effect of being featured in iTunes store compared to songs with comparable previous download ...
2
votes
2answers
78 views

Weighting words based on position in text

I'm currently working on semantic analysis and had a question about text organization and structure. Are there any algorithms, or statistical / machine-learning models that weight the importance of a ...
0
votes
0answers
44 views

Obtaining sequence of lambda values for training glmnet model via `caret`

I have multiple models that I'm training using train in the caret package, all while using the same cross validation folds to ...
0
votes
0answers
24 views

Does it work better to subtract mean of data in logistic regression?

I am using logistic regression to predict $X \rightarrow Y \in \{0, 1\}$ based on the featurization $\phi(X)$. The training objective function is \begin{equation} \mathcal{L} = ...
0
votes
1answer
45 views

Why, when I scale my data set, glmnet gives error?

I'm using glmnet for building the regression models. My data are already log-transformed. when I scale my data set (zero mean, and SD=1), I get the following error: ...
1
vote
0answers
37 views

How to give an input when you are using Machine Learning method in R

I am new to R and machine learning algorithms. I have basic knowledge of different machine learning algorithms. I have four years of daily sales data.I am trying to predict sales using Support Vector ...
0
votes
0answers
15 views

How could I generate an “explanation” for each prediction in a classification ?

I have a classification problem. My classes are 0 and 1. The dataset is a bit big, the training is done on 7 million lines and 100 + variables so I choose to use scikit learn and the logistic ...
0
votes
0answers
35 views

Prediction using Support Vector (SV) method in R

I came to know that using SVM method we can predict the future value more accurately than other normal methods (like ARIMA). My question is how do we give the future index value (let's say 101 when we ...
0
votes
0answers
22 views

GBM, it's overfitting/multicollinearity problem and parameter setting up

I recently came across a predicting problem (0-1 outcome, with more than 80 variables), I decided to use GBM (Gradient Boosting Machine by Friedman)to handle this job. I let the GBM use only 70% of ...