Read the following articles:
• Dario Radečić. 2020. “SHAP: How to Interpret Machine Learning Models With Python, Explainable machine learning with a single function call.” https://towardsdatascience.com/shap-how-to-interpret-machine-learning-models-with-python-2323f5af4be9
• Marco Tulio Ribeiro, Sameer Singh, Sameer Singh. 2016. “Why Should I Trust You? Explaining the Predictions of Any Classifier.” https://arxiv.org/pdf/1602.04938v1.pdf
• Dario Radčić. 2020. “LIME vs. SHAP: Which is Better for Explaining Machine Learning Models? Two of the most popular Explainers compared.” https://towardsdatascience.com/lime-vs-shap-which-is-better-for-explaining-machine-learning-models-d68d8290bb16
• Conor O’Sullivan. 2022. “Squeezing more out of LIME with Python How to create global aggregations of LIME weights.” https://towardsdatascience.com/squeezing-more-out-of-lime-with-python-28f46f74ca8e
• Refer to the SHAP documentation as needed: https://shap.readthedocs.io/en/latest/index.html
• Refer to the LIME documentation as needed: https://lime-ml.readthedocs.io/en/latest/
The key idea behind LIME and SHAP is to provide human-understandable explanations for models, especially black box models such as neural networks and support vector machines. For this assignment, you will be providing only written answers in a Word or PDF document. Based on the aforementioned readings, and any others from the course content, answer the following questions providing proper citations in APA format.
Question Points
1. Write a 1-page explanation of what LIME is, using your own words. Your explanation should include what a local interpretable model is and, more specifically, which types of models are used by LIME.
Question Points
2. Write a 1-page explanation of what LIME is, using your own words. Your explanation should include what a local interpretable model is and, more specifically, which types of models are used by LIME.
3. Using up to 1-page, compare and contrast LIME vs. SHAP. Include the potential pros and cons of each.
4. Writing quality: Avoid spelling mistakes and clearly denote which questions you are answering. Include a reference section in your writeup, and in your text, refer to the references. Follow the APA guidelines for references and citations.

 

 

Sample solution

Dante Alighieri played a critical role in the literature world through his poem Divine Comedy that was written in the 14th century. The poem contains Inferno, Purgatorio, and Paradiso. The Inferno is a description of the nine circles of torment that are found on the earth. It depicts the realms of the people that have gone against the spiritual values and who, instead, have chosen bestial appetite, violence, or fraud and malice. The nine circles of hell are limbo, lust, gluttony, greed and wrath. Others are heresy, violence, fraud, and treachery. The purpose of this paper is to examine the Dante’s Inferno in the perspective of its portrayal of God’s image and the justification of hell. 

In this epic poem, God is portrayed as a super being guilty of multiple weaknesses including being egotistic, unjust, and hypocritical. Dante, in this poem, depicts God as being more human than divine by challenging God’s omnipotence. Additionally, the manner in which Dante describes Hell is in full contradiction to the morals of God as written in the Bible. When god arranges Hell to flatter Himself, He commits egotism, a sin that is common among human beings (Cheney, 2016). The weakness is depicted in Limbo and on the Gate of Hell where, for instance, God sends those who do not worship Him to Hell. This implies that failure to worship Him is a sin.

God is also depicted as lacking justice in His actions thus removing the godly image. The injustice is portrayed by the manner in which the sodomites and opportunists are treated. The opportunists are subjected to banner chasing in their lives after death followed by being stung by insects and maggots. They are known to having done neither good nor bad during their lifetimes and, therefore, justice could have demanded that they be granted a neutral punishment having lived a neutral life. The sodomites are also punished unfairly by God when Brunetto Lattini is condemned to hell despite being a good leader (Babor, T. F., McGovern, T., & Robaina, K. (2017). While he commited sodomy, God chooses to ignore all the other good deeds that Brunetto did.

Finally, God is also portrayed as being hypocritical in His actions, a sin that further diminishes His godliness and makes Him more human. A case in point is when God condemns the sin of egotism and goes ahead to commit it repeatedly. Proverbs 29:23 states that “arrogance will bring your downfall, but if you are humble, you will be respected.” When Slattery condemns Dante’s human state as being weak, doubtful, and limited, he is proving God’s hypocrisy because He is also human (Verdicchio, 2015). The actions of God in Hell as portrayed by Dante are inconsistent with the Biblical literature. Both Dante and God are prone to making mistakes, something common among human beings thus making God more human.

To wrap it up, Dante portrays God is more human since He commits the same sins that humans commit: egotism, hypocrisy, and injustice. Hell is justified as being a destination for victims of the mistakes committed by God. The Hell is presented as being a totally different place as compared to what is written about it in the Bible. As a result, reading through the text gives an image of God who is prone to the very mistakes common to humans thus ripping Him off His lofty status of divine and, instead, making Him a mere human. Whether or not Dante did it intentionally is subject to debate but one thing is clear in the poem: the misconstrued notion of God is revealed to future generations.

 

References

Babor, T. F., McGovern, T., & Robaina, K. (2017). Dante’s inferno: Seven deadly sins in scientific publishing and how to avoid them. Addiction Science: A Guide for the Perplexed, 267.

Cheney, L. D. G. (2016). Illustrations for Dante’s Inferno: A Comparative Study of Sandro Botticelli, Giovanni Stradano, and Federico Zuccaro. Cultural and Religious Studies4(8), 487.

Verdicchio, M. (2015). Irony and Desire in Dante’s” Inferno” 27. Italica, 285-297.

Sample Answer

Sample Answer

 

Title: Understanding the Role of LIME and SHAP in Interpreting Machine Learning Models

Introduction

Machine learning models have become increasingly complex, making it challenging for users to understand how these models arrive at their predictions. In response to this issue, methods like Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP) have been developed to provide interpretable explanations for black box models. This essay aims to explore and compare LIME and SHAP, highlighting their features, applications, and potential pros and cons.

LIME: Local Interpretable Model-Agnostic Explanations

LIME is a technique designed to explain the predictions of any machine learning model by approximating it with an interpretable model locally. In simpler terms, LIME creates a model that is easier to understand for a specific instance or set of instances rather than explaining the entire complex model. This local interpretable model helps users comprehend why a particular prediction was made by the black box model.

LIME mainly uses simple, interpretable models such as linear regression or decision trees to approximate the black box model locally. By generating perturbations around the instance to be explained and observing the output changes, LIME can determine the relative importance of each feature in making the prediction. Through this process, LIME provides insights into the inner workings of the black box model on a local level.

SHAP: SHapley Additive exPlanations

On the other hand, SHAP is based on cooperative game theory and calculates the contribution of each feature to the prediction by considering all possible permutations of features. This method provides a more global perspective on feature importance compared to LIME’s local explanations. SHAP values offer a unified measure of feature importance that is consistent across different instances.

Comparison between LIME and SHAP

When comparing LIME and SHAP, it is essential to consider their respective strengths and weaknesses:

LIME

– Pros:- Provides local interpretability for individual predictions.
– Utilizes simple and interpretable models for approximation.
– Suitable for explaining complex models in a straightforward manner.

– Cons:- May not capture global feature importance effectively.
– Relies on sampling techniques that can introduce variability in explanations.

SHAP

– Pros:- Offers a consistent measure of feature importance across instances.
– Provides a global view of feature contributions to predictions.
– Based on solid theoretical foundations from cooperative game theory.

– Cons:- Computationally intensive, especially for large datasets and complex models.
– May be harder to interpret for non-experts due to its intricate methodology.

In conclusion, both LIME and SHAP play crucial roles in interpreting machine learning models by providing explanations that are understandable to humans. While LIME focuses on local interpretability using simple models, SHAP offers a more global perspective based on cooperative game theory. Depending on the specific needs of the user, either LIME or SHAP can be chosen to gain insights into the black box models’ decision-making processes.

References

– Radečić, D. (2020). “SHAP: How to Interpret Machine Learning Models With Python, Explainable machine learning with a single function call.” https://towardsdatascience.com/shap-how-to-interpret-machine-learning-models-with-python-2323f5af4be9
– Ribeiro, M. T., Singh, S., & Singh, S. (2016). “Why Should I Trust You? Explaining the Predictions of Any Classifier.” https://arxiv.org/pdf/1602.04938v1.pdf
– Radčić, D. (2020). “LIME vs. SHAP: Which is Better for Explaining Machine Learning Models? Two of the most popular Explainers compared.” https://towardsdatascience.com/lime-vs-shap-which-is-better-for-explaining-machine-learning-models-d68d8290bb16
– O’Sullivan, C. (2022). “Squeezing more out of LIME with Python How to create global aggregations of LIME weights.” Link
– SHAP Documentation: https://towardsdatascience.com/squeezing-more-out-of-lime-with-python-28f46f74ca8e
– LIME Documentation: https://lime-ml.readthedocs.io/en/latest/

 

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