Newest 'shap' Questions

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7 views

How can interparet shap.summary_plot and its gray color concerning outliers/anomaly?

I inspired by this notebook, and I'm experimenting IsolationForest algorithm using scikit-learn==0.22.2.post1 for anomaly ...

asked Apr 14 at 18:37

Mario

3191 silver badge12 bronze badges

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votes

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9 views

Are SHAP values additive across examples?

I understand that SHAP values have a property called additivity that means that if you add the SHAP value of each explanatory variable of a particular example to the average prediction of the model on ...

explainable-ai shap

asked Apr 2 at 23:58

user3076574

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vote

0answers

11 views

not getting point predictions from sagemaker clarify [closed]

I wanted to create shap values for my predictions in sagemaker. I found out that I can use "clarify" functionality in sagemaker to get shap values. However, I want to get point predictions ...

aws shap sagemaker

asked Mar 22 at 17:14

Fatima

613 bronze badges

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0answers

18 views

Can I get a global attribution when using Shapley values?

I'm using a shap KernelExplainer to interprete my model and I'd like to display a global attribution for each feature. The idea is to represent, in a numerical way, the plot. What would be the best ...

machine-learning python classification interpretation shap

asked Mar 16 at 11:44

heisenberg

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0answers

30 views

Shapley summary plot interpretation doubt?

I have question when interpreting SHAP summary plot. I have attached the sample plot Here, If I am interpreting it correctly, low values of feature 1 are associated with high and negative values for ...

machine-learning deep-learning r feature-selection shap

asked Mar 9 at 17:40

Raghav Goyal

211 bronze badge

0

votes

0answers

9 views

Explanation on how to interpret force_plot result by using SHAP

I have applied SHAP for explaining the outcome of my neural network. For the force_plot I have obtained the following output when trying to look at multiple ...

neural-network keras explainable-ai shap

asked Mar 1 at 13:10

Sunshine

111 bronze badge

0

votes

0answers

34 views

How to tell which class is which with SHAP values in a summary plot?

I ran a random forest classifier to predict pollen color based on various environmental variables. The possible predictions are purple or yellow. I want to run a summary plot in shapely to get an ...

python shap

asked Feb 28 at 21:35

atudell

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votes

0answers

85 views

How SHAP value explains contribution of features for outliers event?

I'm trying to understand and experiment with how the SHAP value can explain behaviour for each outlier events (rows) and how it can be related to shap.force_plot(). ...

python features explainable-ai shap isolation-forest

asked Feb 17 at 18:36

Mario

3191 silver badge12 bronze badges

0

votes

1answer

16 views

Shapley contribution when coalition is 0

I am exploring Shapley for channel attribution based on [here][1] Consider C1, C2, C3, C4 as 4 channels in question. Some of the coalition does not have value, such as ...

explainable-ai shap

asked Nov 20 '20 at 3:48

Kenny

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1answer

106 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 ...

machine-learning explainable-ai interpretation shap

asked Nov 6 '20 at 14:17

David Masip

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1

vote

0answers

28 views

Passing reduced/different feature data to LimeTabularExplainer compared to the original model

I am trying to use LimeTabularExplainer class and explain_instance function to find explainations of my LightGbm (lgb) model. However, the lgb model uses complex feature set which are not ...

python explainable-ai shap lime

asked Oct 7 '20 at 10:04

the M

112 bronze badges

5

votes

1answer

182 views

How to achieve SHAP values for a CatBoost model in R?

I'm asked to create a SHAP analysis in R but I cannot find it how to obtain it for a CatBoost model. I can get the SHAP values of an XGBoost model with ...

machine-learning classification r shap catboost

asked Jul 22 '20 at 7:08

user100740

712 bronze badges

2

votes

0answers

160 views

Explain FastText model using SHAP values

I have trained fastText model and some fully connected network build on its embeddings. I figured out how to use Lime on it: complete example can be found in Natural Language Processing Is Fun Part 3: ...

python nlp pytorch shap fasttext

asked Jun 18 '20 at 14:09

Mikhail_Sam

1214 bronze badges

0

votes

0answers

38 views

Ways to visualize the outcome of machine learning interpretability techniques (for image classification)

“Machine Learning Interpretability” or “Explainable Artificial Intelligence” has become quite popular in the machine learning community and in recent research. The goal is to make complex (deep ...

image-classification explainable-ai shap lime

asked Jun 10 '20 at 9:55

randy_marsh

11 bronze badge

1

vote

0answers

41 views

Aggregate SHAP importances from different models

A couple of questions on the SHAP approach to the estimation of feature importance. I would like to use the random forest, logistic regression, SVM, and kNN to train four classification models on a ...

decision-trees explainable-ai predictor-importance shap

asked May 20 '20 at 16:01

CaffeineMan

113 bronze badges

3

votes

1answer

1k views

How is the “base value” of SHAP values calculated?

I'm trying to understand how the base value is calculated. So I used an example from SHAP's github notebook, Census income classification with LightGBM. Right after I trained the lightgbm model, I ...

lightgbm explainable-ai shap

asked May 4 '20 at 23:09

David293836

1576 bronze badges

1

vote

1answer

265 views

Getting the positive impacting features using SHAP

I'm attempting to use SHAP to automatically extract feature names that have a positive impact on my regression models. On inspection of the code I see that the bar plot, for example, determines these ...

features shap

asked Apr 29 '20 at 9:56

amateurjustin

551 silver badge5 bronze badges

1

vote

0answers

37 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 ...

machine-learning explainable-ai interpretation shap

asked Apr 13 '20 at 16:56

giogix

1535 bronze badges

2

votes

1answer

54 views

treeExplainer algorithm intuition

I'm reading the paper about the treeExplainer; the pseudo-code of Algorithm 1 is a bit cryptical as most of the variables are not even defined (same with sampling and all details involved). Is there a ...

random-forest decision-trees xgboost explainable-ai shap

asked Apr 8 '20 at 11:19

zzzbob

212 bronze badges

1

vote

0answers

32 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-...

decision-trees prediction interpretation shap

asked Mar 31 '20 at 14:02

room13

1334 bronze badges

1

vote

0answers

125 views

Tree Path Dependent expected value

I stuck on this topic for couple days and seems I need your help to understand what is expected value in TreeExplainer when feature_perturbation = tree_path_dependent, precisely what is expected value ...

explainable-ai shap

asked Mar 3 '20 at 11:54

jacekblaz

111 bronze badge

2

votes

1answer

280 views

How to calculate joint feature contribution for XGBoost Classifier in python?

I referred to this beautiful document to research about joint feature contibutions. But this works only for RandomForest algorithms because of treeinterpreter (does ...

machine-learning python xgboost shap

asked Feb 3 '20 at 19:58

Sudhakar Samak

313 bronze badges

0

votes

0answers

540 views

SHAP Kernel explainer for my pipeline model

I am trying to use SHAP kernel explainer to understand my XGBOOST model. My data is the lending club data and I am trying to predict the Grade of each customer. The data contains different types of ...

machine-learning xgboost machine-learning-model pipelines shap

asked Jan 27 '20 at 9:37

Omar Baz

534 bronze badges

5

votes

2answers

949 views

SHAP value analysis gives different feature importance on train and test set

Should SHAP value analysis be done on the train or test set? What does it mean if the feature importance based on mean |SHAP value| is different between the train and test set of my lightgbm model? ...

features lightgbm predictor-importance shap

asked Oct 7 '19 at 19:10

pbk

533 bronze badges

3

votes

1answer

873 views

Explanation of how DeepExplainer works to obtain SHAP values in simple terms

I have been using DeepExplainer (DE) to obtain the approximate SHAP values for my MLP model. I am following the SHAP Python library. Now I'd like learn the logic behind DE more. From the relevant ...

neural-network deep-learning explainable-ai shap

asked Aug 27 '19 at 8:20

mlee_jordan

1311 silver badge6 bronze badges

3

votes

1answer

236 views

Is it valid to compare SHAP values across models?

Let's say I have three models: a random forest with 100 trees a random forest with 1000 trees an xgboost model. I can rank the importance of my features on my dataset for each model using SHAP, and ...

explainable-ai shap

asked Aug 10 '19 at 21:55

DKL

563 bronze badges

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Questions tagged [shap]

How can interparet shap.summary_plot and its gray color concerning outliers/anomaly?

Are SHAP values additive across examples?

not getting point predictions from sagemaker clarify [closed]

Can I get a global attribution when using Shapley values?

Shapley summary plot interpretation doubt?

Explanation on how to interpret force_plot result by using SHAP

How to tell which class is which with SHAP values in a summary plot?

How SHAP value explains contribution of features for outliers event?

Shapley contribution when coalition is 0

Shapley values without intercept (or without `expected_value`)

Passing reduced/different feature data to LimeTabularExplainer compared to the original model

How to achieve SHAP values for a CatBoost model in R?

Explain FastText model using SHAP values

Ways to visualize the outcome of machine learning interpretability techniques (for image classification)

Aggregate SHAP importances from different models

How is the “base value” of SHAP values calculated?

Getting the positive impacting features using SHAP

Can we use Shap to interpret output changes?

treeExplainer algorithm intuition

Difference between shap values and feature contributions

Tree Path Dependent expected value

How to calculate joint feature contribution for XGBoost Classifier in python?

SHAP Kernel explainer for my pipeline model

SHAP value analysis gives different feature importance on train and test set

Explanation of how DeepExplainer works to obtain SHAP values in simple terms

Is it valid to compare SHAP values across models?

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Questions tagged [shap]

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