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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 ...
Funkwecker's user avatar
6 votes
1 answer
436 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 ...
David Masip's user avatar
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5 votes
1 answer
2k 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 ...
J.D.'s user avatar
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5 votes
2 answers
166 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 (...
Hasan Sohail's user avatar
4 votes
1 answer
229 views

Why do Shapley value solutions remain consistent when the value function of the empty set changes in the ML context?

Hey there data science stack exchange - question about SHAP. In the original Shapley value formulation from Lloyd, one assumption is that the value function of the empty set equals zero, $v(\emptyset) ...
shay's user avatar
  • 143
3 votes
1 answer
359 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 ...
PicaR's user avatar
  • 314
2 votes
2 answers
4k 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 ...
codeananda's user avatar
2 votes
3 answers
1k 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 ...
Selvam's user avatar
  • 93
2 votes
2 answers
237 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.
Aaron's user avatar
  • 201
2 votes
3 answers
445 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 ...
Jayden Rice's user avatar
2 votes
1 answer
109 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 ...
CoolJohnTo's user avatar
2 votes
0 answers
48 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 ...
xan's user avatar
  • 121
2 votes
0 answers
254 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/...
Tpeeters's user avatar
2 votes
1 answer
31 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., ...
n.baes's user avatar
  • 39
2 votes
0 answers
130 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 ...
Ali Raza Memon's user avatar
1 vote
2 answers
646 views

A neural network with more output neurons than labels

When we train a neural network model for a classification problem, we usually have a dense output layer of a size equal to the number of labels (classes) we have. If the layer size was greater, the ...
Abdulrahman Bres's user avatar
1 vote
1 answer
184 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 ...
Paw in Data's user avatar
1 vote
1 answer
143 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 ...
PicaR's user avatar
  • 314
1 vote
3 answers
303 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 ...
Subhash C. Davar's user avatar
1 vote
1 answer
39 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 ...
Kusisi Karem's user avatar
1 vote
1 answer
39 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 ...
Vintagefiretruk's user avatar
1 vote
1 answer
43 views

Am I suppose to do any statistical test on results?

I am doing an email campaign. Before sending emails to users I divided my user base into treatment and control groups (50-50). Divided the groups in such a way that no difference in user behaviour. I ...
udaykumar gajavalli's user avatar
1 vote
0 answers
34 views

Standard Error interpretation help

I performed a standard error on my machine learning model to predict protein structure. The graph Im showing here is a snippet of the actual data and I deleted some irrelevant info. The y axis is the ...
hypermiler3's user avatar
1 vote
0 answers
27 views

Is there a statistical test for comparing my dataset percentages with published percentages?

I have a clinical dataset which is showing the percentage of A is 57% and B is 35% for where an tumours is initially found. However the literature is showing it is A is 73% and B is 23%. Is there a ...
Matt Smith's user avatar
1 vote
1 answer
196 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 ...
No-Time-To-Day's user avatar
1 vote
1 answer
106 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. ...
Polaster's user avatar
1 vote
1 answer
33 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. ...
Zilfalon's user avatar
1 vote
0 answers
68 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 ...
User2321's user avatar
  • 111
1 vote
0 answers
38 views

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 ...
pinky's user avatar
  • 151
1 vote
2 answers
1k 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 ...
grumpyp's user avatar
  • 157
1 vote
1 answer
63 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 ...
mrgou's user avatar
  • 133
1 vote
0 answers
62 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 ...
giogix's user avatar
  • 163
1 vote
0 answers
42 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.
Subhash C. Davar's user avatar
1 vote
0 answers
146 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-...
room13's user avatar
  • 133
0 votes
2 answers
172 views

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 ...
Connor's user avatar
  • 661
0 votes
2 answers
718 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 ...
Shrinidhi M's user avatar
0 votes
1 answer
1k 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 ...
Mara Bella's user avatar
0 votes
1 answer
29 views

SHAP values are explaining the wrong output value

I was checking the local accuracy property of the SHAP values. It states that for a data point $(X,y)$, the SHAP values $(s_1,s_2,s_3,...)$ of features $(x_1,x_2,x_3,...)$ sum up to the difference of ...
Abhay Gupta's user avatar
0 votes
1 answer
839 views

ValueError: X has 54 features, but DecisionTreeClassifier is expecting 53 features as input

I am analysing and prediction 2023 Cricket World Cup based on previous given dataset. This is Exploratary analysis: Feature selection and Training model: Applying Random forest classifier algorithm: ...
Mithlesh Upadhyay's user avatar
0 votes
1 answer
42 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 ...
F.Hazratian's user avatar
0 votes
1 answer
29 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 <...
john22's user avatar
  • 147
0 votes
1 answer
30 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 ...
a_jelly_fish's user avatar
0 votes
1 answer
79 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 ...
SpiderRico's user avatar
0 votes
0 answers
15 views

Interpreting Centered 2-Way PDP

I have recently used scikit-learn's PartialDependenceDisplay.from_estimator function to display cICE plots in combination with PDPs using the ...
Guest's user avatar
  • 21
0 votes
0 answers
20 views

Which method is better to understand key drivers/feature importance in prediction?

After applying two different classifiers (EBM Classifier and Random Forest Classifier) and getting similar scores, I used InterpretML functionality to identify the most relevant features in each model....
Guilherme Atihe de Oliveira's user avatar
0 votes
0 answers
46 views

What does the shap interaction value of a feature with itself mean?

SHAP allows us to compute interaction effects by considering pairwise feature attributions. This leads to a matrix of attribution values representing the impact of all pairs of features on a given ...
figs_and_nuts's user avatar
0 votes
0 answers
17 views

What is the complexity of ICE (Individual conditional expectation) on ensemble trees

I'm evaluating different model-agnostic methods on gradient boosting or random forest model. For Shapley, specifically TreeSHAP, the complexity is O(TLD^2) according to Lundberg et al. 2018. T: #trees,...
wealthh2's user avatar
0 votes
0 answers
12 views

How to specify and interpret control variables in the model?

I'd like to build a classification model on customers across different countries, but not sure how to interpret the coefficient of those countries and other features, especially features that could be ...
Iris's user avatar
  • 3
0 votes
0 answers
15 views

What does positive value in LIME mean?

I'm exploring the workings of LIME in NLP models to understand how it elucidates positive and negative words. I possess a trove of documents resembling this excerpt: The UN children’s agency says the ...
asmgx's user avatar
  • 549
0 votes
0 answers
52 views

Help with multinomial logistic regression

I am a data science student and have the opportunity to work on an article regrading cardiac arrests in our country. For now I performed the multinomial regression model and I also plan on doing a ...
Ni Vaznu's user avatar