Questions tagged [interpretation]

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Which intrinsically explainable model has the highest performance?

Explainable AI can be achieved through intrinsically explainable models, like logistic and linear regression, or post-hoc explanations, like SHAP. I want to use an intrinsically explainable model on ...
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1 answer
30 views

Efficient ways of clustering for big data

I have a task which is customer segmentation with 120k users and a record of their purchases which is +3 million records of data, the approach I want to use is to use clustering algorithms like kmeans ...
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0 answers
7 views

Neural net: linear surrogate model performs better than "ex ante" linear model

I try to predict something with a feed-forward neural network. More specifically, I fit 5 neural nets and take the average of the predictions - this is then my ...
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SHAP: How can interpret a certain feature has positive or negative impact correctly?

I want to raise a question here already I created an issue in the related workaround but still haven't gotten any clarification about it. I also want to tag most related posts I found: post1 & ...
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2 answers
37 views

How do I combine two different measures of correlation coefficients?

In the dataset, we have a numerical feature and a numerical target. We are calculating the Pearson coefficient and Spearman rank correlation. Pearson to track the linear relationship and Spearman to ...
1 vote
1 answer
34 views

Interpreting model

If I trained a model (say logistic regression) on train, test and validation. During interpretation which dataset (test or validation) should I base on for interpretation? If test and validation shows ...
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13 views

How to calculate feature contribution to regressor error in an anomaly detection problem?

Say I have a standard regressor, such as an elastic net model, used to detect anomalies in a system. I am predicting target sensor T, with feature A, B, C, which are upstream sensors of sensor T. What ...
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20 views

How to explain the high accuracy and F1 score on the test set with a huge binary crossentropy loss?

I'll provide a little of introduction based on my example. I have a small collection of RGB (but 'gray-looking') brain MRI photos, divided into 2 classes: healthy and tumor. My data split looks like ...
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0 answers
15 views

How "much" should belief be weighted against numerical measures of accuracy/correctness?

How "much" should belief be weighted against numerical measures of accuracy/correctness? It's possible to devise numerically low-quality models, but that have very good empirical validity, ...
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What are some "best practices" for discovering true patterns in data without relying on "scores" as measures of accuracy?

What are some "best practices" for discovering true patterns in data without knowing about them and without relying on "scores" as measures of accuracy? In university I was always ...
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1 vote
1 answer
17 views

Interpreting visualisations for write ups - clustermaps

I produced a clustermap as part of an attempt to visualise any multicollinearity in a dataset and it's occurred to me that I actually don't really know how to interpret it. There is plenty of ...
2 votes
0 answers
19 views

When is scaling and centering important?

There are some models such as PCA or SVM where scaling and centering of training data is essential. There are some models, mostly tree-based where scaling and centering is not required at all. I don't ...
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1 vote
1 answer
62 views

How to interpret a linear regression effects graph?

could someone tell me how to interpret the following graph? It corresponds to a graph in which the effects of the variables in a linear regression are observed, but its interpretation is not clear to ...
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0 answers
6 views

Interpretation of agnostic models

I am trying to interpret a black box model. This model is a random forest that I am using to make predictions. I have read that LIME is a way to interpret black box models, but I don't quite know how ...
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3 votes
1 answer
224 views

Interpreting ROC curves across k-fold cross-validation

I have used a MARS model (multivariate adaptive regression splines) and I have used k fold cross validation for the evaluation of the model, obtaining the following graph: How would be the ...
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How can I disaggregate the impact of a group of variables using machine learning?

I have a problem where the target variable Y (continuous, values: 0-1) is controlled by large number of variables. These variables can be grouped by the nature of the data: ...
1 vote
1 answer
60 views

Correlation analysis yields conflicting results. Positive Pearson and Negative Spearman

I have four features x1,x2,x3,x4. All of their correlation with y are similar in Pearson correlation and in Spearman rank correlation separately. However, all these are +0.15 in Pearson and -0.6 in ...
0 votes
1 answer
181 views

how to visualize segmented labels in a already existing graph?

I am working on a project where I have to segment the image using multi-class segmentation (3 classes) on microscopic images. Now let's say that I am segmenting solid, liquid and gas images (this is ...
1 vote
1 answer
66 views

Why do I get this result with a chi- square test?

I have a question about the chi squared independence test, I'm working on dataset and I'm interested in finding the link between the categories of product and the gender, I plot my contingency table. ...
1 vote
1 answer
27 views

Practical Interpretation of PCAs for a supplier analysis

I am using PCA to validate and research a set of 13 suppliers of products against a set of about 50 variables and performance indicators against an ideal "wish"-Supplier, mostly based on G. ...
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1 answer
22 views

Answering the question of "WHY" using AI?

We have seen lots of natural occurrences that are happening in the whole world. Since we have great progress in technology and in particular AI, How can I employ <...
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2 votes
0 answers
136 views

Shapley values for channel attribution equal to linear attribution

I am looking into Shapley values for online marketing attribution. In recent time many articles seem to have been made on this particular approach to attribution (there are more): https://medium.com/...
1 vote
0 answers
47 views

Understanding, visualizing and interpreting CNN activations

I am working with the first layer of a CNN and trying to understand how to interpret the activation output. My CNN takes input from 3 channels (RBG picture) and the first layer is ...
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0 votes
1 answer
375 views

Can absolute or relative contributions from X be calculated for a multiplicative model? $\log{ y}$ ~ $\log {x_1} + \log{x_2}$

(How) can absolute or relative contributions be calculated for a multiplicative (log-log) model? Relative contributions from a linear (additive) model E.g., there are 3 contributors to $y$ (given by ...
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2 votes
2 answers
105 views

What are available Python libraries for Interpretable ML?

I recently become familiar with Interpretable ML and I found some libraries like LIME. I would be thankful if you can suggest to me some libraries and what are the advantages of each library.
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1 vote
0 answers
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paired t-test shows no difference between median and Wilcoxon test p value shows that there is a difference between median values ? How to interpret?

I have a dataset. I wanted to do paired t test on it. So I carried out normality test and it showed that it does not follow normal distribution. So I used Wilcoxon test in place of paired t test. The ...
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1 vote
1 answer
854 views

How to interpret my logistic regression result with statsmodels

so I'am doing a logistic regression with statsmodels and sklearn. My result confuses me a bit. I used a ...
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2 votes
1 answer
22 views

Suggestions for improvement? Time series of variation in relative frequency of emotion-related words in academic psychology over time

First time plotting and interpreting time series data and I have used a line plot for ease of use. I am aware this is incredibly basic, but any input/ recommendations would be much appreciated (e.g., ...
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0 votes
1 answer
25 views

How to increase sales and revenue of a Client?

I was asked this in an interview for a Data Scientist position: Lets say Holland and Barret came to you and said they'd like to increase their sales and revenue. How will you go about it? My answer ...
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5 votes
1 answer
254 views

Shapley values without intercept (or without `expected_value`)

I have a model and I want to derive its interpretability by using feature contributions. In the end, I want to have some contribution per feature such that the sum of contributions equals the ...
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1 vote
1 answer
158 views

Is there an intuitive interpretation of precision always higher than recall?

I have a multiclass-classifier whose macro-precision is always greater than macro-recall. I suppose it means false negatives outnumber false positives in general. Is there an intuitive interpretation ...
-1 votes
1 answer
52 views

Machine learning, speech recognition technologies for Sound of Animals interpretation [closed]

https://www.google.com/search?q=sound+of+animals&client=ms-android-lava&prmd=inv&sxsrf=ALeKk02xrn0-yn-FZSkidTogB4l4B_TH6A:1600539091086&source=lnms&tbm=isch&sa=X&ved=...
0 votes
1 answer
615 views

How to interpret KDE distribution graph?

I would like to know how to interpret this distribution graph. I have been doing an exercise from the book called 'Python for Finance Cookbook' by Eryk Lewinson. It does not give an in-depth ...
0 votes
1 answer
33 views

Types of maps in Interpretable Machine Learning

I have worked on Interpretable Machine Learning (IML) for over 1 year. However, there are some terminologies that always make me confused. For example, saliency maps/heat maps. Are they same? Are ...
2 votes
2 answers
2k views

How do standardization and normalization impact the coefficients of linear models?

One benefit of creating a linear model is that you can look at the coefficients the model learns and interpret them. For example, you can see which features have the most predictive power and which do ...
2 votes
3 answers
214 views

How do I interpret the output of linear regression model in R?

I have the following linear regression model and its analysis. There are a few errors, but I am not very sure about the errors. I have not succeeded in finding them so far. First, the 95% confidence ...
1 vote
1 answer
51 views

Identify significant features in clustering results

I'm a student in Data Analysis, working on a data clustering exercise. Two clusters have been identified based on a dataset with 40 features. To interpret and label these clusters, I'm wondering if ...
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0 votes
0 answers
37 views

What methods to get the intention behind questions (time, preferences, ...)?

I have a csv with different questions, answer and question types. So far I have only been able to differentiate the questions between muliple answers and likert scale. I would rather like to get the ...
1 vote
3 answers
206 views

Does Karl Pearson correlation indicate linear relationship between two variables?

Wikipedia and literature do not seem to convey correct interpretation of Karl Pearson correlation. Also, some of the authors interpret it as a linear correlation or association. To me it simply tells ...
1 vote
0 answers
43 views

Can we use Shap to interpret output changes?

Can we calculate the difference between Shapley values to interpret changes in the output? More precisely, if we get Shapley values for two different inputs, can we compare them to understand how much ...
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2 votes
0 answers
125 views

Understanding CNN by visualizing class activations using GRAD_CAM

I followed the blog Where CNN is looking? to understand and visualize the class activations in order to predict something. The given example works very well. I have developed a custom model using ...
1 vote
0 answers
41 views

Professionals appear to interpret sample correlation (e.g. Karl Pearson) as if it represents linear correlation. Is it the correct interpretation? [closed]

I am stressed following the wrong interpretation. What is the correct way of understanding a correlation coefficient.
1 vote
0 answers
86 views

Difference between shap values and feature contributions

I always found both concepts a bit confusing since they are quite similar. Would someone provide clear example where to apply each? Shap values ref: https://towardsdatascience.com/explain-your-model-...
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0 votes
1 answer
63 views

Feature-to-parameter mapping in neural networks

For neural networks, can we tell which parameters are responsible for which features? For example, in an image classification task, each pixel of an image is a feature. Can I somehow find out which ...
19 votes
5 answers
5k views

What is the difference between explainable and interpretable machine learning?

O’Rourke says that explainable ML uses a black box model and explains it afterwards, whereas interpretable ML uses models that are no black boxes. Christoph Molnar says interpretable ML refers to the ...
1 vote
1 answer
84 views

Drastic drop in Somers' D ? Why?

I came across to find the correlation between the ratings assigned by two coaches to a same group of 40 players. I have tabulated the results as below: The Somers' D is 50%. However, for the case ...
2 votes
2 answers
541 views

How to interpret Correlation along with Coefficients of multiple linear regression ?£

I have 10000 samples. There are 4 independent variables and 1 dependent variable. The independent variables are all centered with 0 mean. I found the correlation coefficients between each of these ...
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5 votes
1 answer
1k views

How do I interpret loss in a neural network?

I am studying how to evaluate the performances of a convolutional neural network, and in particular I have seen that we have to look both at accuracy and loss. I don't understand why do we have to ...
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5 votes
2 answers
135 views

How to interpret two continous variables output using GAM?

I really need help with GAM. I have to find out whether association is linear or non-linear by using GAM. The predictor variable is temperature at lag0 and the output is cardiovascular admissions (...
1 vote
2 answers
402 views

More output neurons than labels?

When we train a neural network model for a classification problem, we usually have a dense output layer of size equal to the number of labels we have. If the layer size was greater, the model can ...