Validation is the process of assessing whether the results of an analysis are likely to hold outside of the original research setting. DO NOT use this tag for discussing `validity` of a measurement or instrument -- such as that it measures what it purports to.

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1answer
16 views

How to address edge relations between training set and test set?

Suppose we are working on some sort of classification problem, and we have subdivided our data into a training set and a test set (or validation set, or etc.). We wish to prepare the data in the ...
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0answers
16 views

Why classification accuracy in validation set gets lower if validation cost also gets lower?

I'm training neural network for some simple classification task using tensorflow and have 2 output neurons, using softmax classification. My question is why accuracy on validation set gets lower when ...
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1answer
1k views

Within-group sum of squares of cluster

I have a multivariate dataset for which I have only a table including the cross-wise Euclidean distances between all points and a list giving the assignment of each point to one of several clusters. ...
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0answers
14 views

statistical tolerance

My request is: I have data (sums of money) and someone calculated tolerance limits for the data. I want to validate these tolerance limits with statistical methods/arguments. Does anyone know ...
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2answers
148 views

highly sporadic validation error during training with multilayer perceptron

I'm encountering an issue where a classifier I'm developing reports validation errors during training that span a wide range of values without consistently decreasing over time. Unfortunately, I'm new ...
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1answer
104 views

The effect of oversampling on the positive predictive value

I need to calculate the positive predictive value for a validation set for a rare event. The problem is that the validation set was oversampled for the rare event. The event occurs in 5 percent of the ...
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0answers
20 views

ARIMA model over- or underfitting: compare training and validation performance

I'm doing research using seasonal and nonseasonal ARIMA models. Here's the result of model identification: Based on many sources, Your model is overfitting your training data when you see that ...
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0answers
10 views

A new formula to estimate seminal vesicle volume? Which method to validate it?

I developed a new formula to estimate seminal vesicles volume, and tried it on 75 cases. I want to compare this new formula-method with golden standard method? I think i can use correlation(Pearson) ...
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0answers
30 views

How to validate a Poisson GLMM model?

I’m using the glmer function from the lme4 package in R to model species richness adjacent ...
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0answers
19 views

Self Organizing Map and input normalizing

I've been playing around with self organizing maps (SOM) recently. I tried to implement a simple example. You can see the training implementation function gist here and full contained SOM example ...
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1answer
481 views

Prediction evaluation metric for panel/longitudinal data

I would like to evaluate several different models that provide predictions of behavior at a monthly level. The data is balanced, and $n=$100,000 and $T=$12. The outcome is attending a concert in a ...
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0answers
21 views

Comparing a regression model with a single unit to the original model with all units

Background information: I have a regression model consisting of 230 companies (entity) for 20 years The model has 9 X-variables, and the P-value < 1% for the whole model The ...
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2answers
92 views

Model fitting: resampling the validation set to obtain distributions of test statistic

I see many descriptions of splitting the data set into a training part, a validation part and a test part. We train our models on the training part and choose the best model using the validation part, ...
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1answer
208 views

Minimal number of samples/conversions for statistical validity

We are measuring conversion rates (% of visitors who bought) on an e-commerce site. The test apply to a segment of visitors who meet specific criteria (for example people from a certain country). ...
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0answers
9 views

CNN training and overfitting

When testing the training of a CNN code with a small data set (approx 2560 images each for training and validation), what is over-fitting and how can it be mitigated? Arnold
3
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1answer
247 views

Validation of a questionnaire in a new population

I have 400 responses to a 20 item questionnaire which purports to measure an attitudinal constuct in medical students. The instrument was validated in the US for a single year of medical students and ...
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2answers
26 views

Validation set in presence of cross-validation

I am new to machine learning and want to ask regarding a confusion I have. I have a data set which is labeled and I want to do supervised learning. My question is related to cross-validation and ...
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0answers
17 views

why don't my CNN validation errors decrease?

I'm running theano_alexnet. I found that with greater numbers of iterations (20,000) the training cost and training error rates began to decrease (6.9 to 4.9 and 99% to 93%, respectively).When I ...
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0answers
26 views

R: Interpreting Fowlkes–Mallows index output for comparing dendrograms for hierarchical clustering

I have two data sets which contains information about subsystems in a bacterial metabolic model DataSet1: Behavior data of the subsystems DataSet2: Structural data of the same subsystems Then perform ...
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1answer
42 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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2answers
58 views

Classification accuracy increasing while overfitting

I'm training a classification model, and these are the plots for accuracy and loss history. Besides the fact that the learning rate is too large, what I understand is that the model start ...
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1answer
24 views

validating model in machine learning - what does it mean in reality (intuition)

Could someone explain (in simple way) what does mean of validating model ? I tried to understand it, but I didn't managed to. I can do cross-validation, but I am not sure about if it is ...
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0answers
8 views

How to summarize MSE across groups?

I have a large amount of time series data collected for different groups over a 30 year period (dataset x) that can be broken down by sub-group. and corresponding time series data (dataset y) from a ...
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0answers
20 views

When I can say a dataset is imbalanced?

I have a data set with only two outputs: positive and negative The ratio of positive:negative is 3.5:1 In this case, is my data set unbalanced? If so, what metric I should use to report the ...
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0answers
11 views

Does it make sense to use my in-sample data to look at goodness of fit for my model?

Basically, I came across an article where the authors first ran a logistic regression on a data set to predict the probability (q=demand) of buying their product, as a function of price p and various ...
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1answer
28 views

Topic Modeling Dataset for Code Verification

I am trying to write up a Gibbs sampling Latent Dirichlet Allocation function for myself in R, and wanted to run it on a dataset where the true classification of ...
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0answers
53 views

Cluster validation method for no cluster labels and differently sized clusters

I'm primarily a programmer and have little to no training in formal maths or statistics of any kind. I'm working on my dissertation (which foolishly is about clustering data), the process is ...
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0answers
32 views

Can I use the Xie-Beni index to validate data transformation parameters in fuzzy c-means clustering?

I am using fuzzy c-means algorithm to cluster my data in various feature spaces and the results differ depending on what kind of transformation I perform on my raw data. I want to know if using the ...
2
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1answer
57 views

Can we gain by merging validation and test set?

Reading this, Cross-validation including training, validation, and testing. Why do we need three subsets? I realized that if we can reduce the variance of the model performance, I wouldn't need the ...
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0answers
23 views

How to bootstrap validate regression model that involves removing outliers?

Suppose I have the following modelling process: Fit simple linear regression to whole data. Identify outliers, in the sense of having studentized residuals greater than a threshold, and remove them. ...
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0answers
17 views

External validation of a group's machine learning process

Say there's a group (that is opaque to you) that's heavily using machine learning methods to produce some outputs. You don't have access to their input data or code but can ask high level questions ...
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13 views

What sort of cross validation is this?

I've always tested my classification techniques using non-standardised trial and error but I'm interested to see which category my techniques fall under. They seem to fall under several but I'm not ...
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2answers
21 views

What do we learn from a test set?

Suppose I split my data into two parts -- a training set (having 80% of my data) and a testing (20%) set. I train a model on my training set, and test it on the test set. What do we learn from ...
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3 views

Validation of prediction interval for count data

I have developed a random-effects (frailty) survival model for repeated events which enables calculating individual-specific mean and prediction interval for the cumulative incidence (rate) of future ...
3
votes
1answer
42 views

Calculate Brier score and cindex for AFT model in R

While with Cox PH model, package pec in R provides several useful functions to validate the models based on cindex and brier score, with AFT model, pec does not support object with class survreg. Is ...
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1answer
100 views

cross validation and validation( to find RMS error and correlation ) in matlab

Dear Experts; i have text data (sample points are 324) of different climatic parameters. 3rd column of each text file was contained some missing or NaN data. Using Scatter data interpolation in ...
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13 views

How to find the accuracy of a multiple linear regression model against existing dataset ?`

I need to make a statement of accuracy of my predictive model against existing dataset , how should I proceed ahead with it?
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2answers
452 views

What is a good way to test a simple Recurrent Neural Network

I have coded up a simple real-value regression RNN in theano. What kind of dataset should I test it on? How should I go about testing it? My structure is: Univariate (for now) timeseries, ...
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5answers
9k views

Hold-out validation vs. cross-validation

To me, it seems that hold-out validation is useless. That is, splitting the original dataset into two-parts (training and testing) and using the testing score as a generalization measure, is somewhat ...
3
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1answer
3k views

Classification score for Random Forest

I'm learning about the Decision Tree and Random Forests. But there is something I don't really understand. I have a training set and a cross-validation set. I need to train different Random Forests, ...
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0answers
42 views

Computing c-index for an external validation of a Cox PH model with Stata

I have developed a Cox prognostic model based and internally validated it using bootstrapping. I also evaluated its calibration using Harrell’s $c$ statistic and Somers' $D$. I have also checked ...
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0answers
35 views

How to split training data for parameter tuning and accurate out-of-sample predictions

I am currently working on a kaggle competition; ignoring the details, each training & test set example, in this competition, essentially consists of product and search term pairs. Given each of ...
3
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1answer
38 views

Random Sample Validation

This is a real life scenario where I have just assumed responsibility for a new team The results of my team who perform legal contract abstractions are audited each month by our client using random ...
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0answers
19 views

Calibration test of cox-model in external validation using stata

I'm planning to validate a cox-risk prediction model in external dataset. As a pert of the validation process, I want to test the calibration of my model in the external dataset. I would appreciate if ...
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0answers
19 views

Reposted: Calibration and Discrimination of Cox prognostic model with Stata [duplicate]

I'm planning to do an external validation of a Cox-prognostic model against another study and a published risk prediction equation. Yet, my previous exposure is limited validation of logistic model. ...
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0answers
20 views

nltk: odd outputs from bleu_score

For machine translation purposes I use bleu score, which seems to be the validation mechanism of choice (used in the sutskever 2014 sequence-to-sequence). The purpose is to get as high bleu as ...
6
votes
1answer
92 views

How to account for case weights when generating folds for K-fold CV?

I am currently working on a binary classification problem where each point in the dataset is paired with a case weight. Specifically, each record $(w_i, x_i, y_i)$ represents a distinct type of ...
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0answers
29 views

Should difference between accuracy of model on training data and testing data be considered for model selection?

Suppose I have two models (Model 1 and Model 2), Where Accuracy of Model 1 on test data is higher than that in Model 2 Difference between accuracy of model on test data and training data is higher ...
0
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1answer
38 views

Choosing number of samples to train a model

(On behalf of a colleague) I have performed some modelling based on a naïve Bayes classifiers model (weighted genomic risk score) and obtained reasonable ROCAUC results (used ROCR, pROC, and SDMtools ...
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2answers
57 views

Which balance strategy to learn from my very imbalanced dataset?

I'm using a deep learning approach on a dataset made of ~20 millions of elements, where each element has a TRUE or FALSE label. This dataset unfortunately is veeery imbalanced: I've 98% of falses and ...