Shooting gams

Might want to use Anaconda to decompile those if they're Games Factory 2 / MMF2 era games. #9 Hope this ain't too much of a necropost (last post was January of this year at least), but what happens/does it mean if the Clickteam file gets a "stop status encountered" error when trying to extract? #10 Hope this ain't too much of a necropost (last post was January of this year at least), but what happens/does it mean if the Clickteam file gets a "stop status encountered" error when trying to extract? Doesn't sound good though, maybe the .MFA file is incompatible with that version? #11 Aha, Beavis & Butthead, another man of culture! ;)It is quite a sporadic error, as there's no pattern as to which .cca/TGF .gams it seems to pop up on, out of the files I've tried the Extractor on. #12 Aha, Beavis & Butthead, another man of culture! ;)It is quite a sporadic error, as there's no pattern as to which .cca/TGF .gams it seems to pop up on, out of the files I've tried the Extractor on. that's what I'm gonna guess then, I don't think anaconda can decomp the absolute latest stuff afaik?

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Into overall model behavior and local explanations for individual predictions.At the interpretable end of the spectrum, lenders can opt for models that are inherently transparent by virtue of their simple, linear structure. Examples include:Logistic regressionDecision rules Explainable Boosting Machines (EBMs)Generalized Additive Models (GAMs)What these "glass box" models sacrifice in accuracy, they make up for in intuitive explanations. A logistic regression credit model, for instance, outputs a simple linear equation where the impact of each input variable on default probability is immediately apparent from its coefficient. To boost the performance of these interpretable models, researchers have proposed techniques like EBMs and GAMs that introduce some nonlinearity while preserving explanatory power. Google‘s InterpretML package offers open-source implementations.For cases where the superior accuracy of a complex model is needed, post-hoc XAI techniques can help users make sense of predictions without sacrificing performance. Popular methods include:SHAP (SHapley Additive exPlanations): Measures the marginal contribution of each feature to a prediction by computing Shapley values. Can produce both global feature importance plots and local explanations in the form of force plots.import shapexplainer = shap.TreeExplainer(xgb_model)shap_values = explainer.shap_values(X)shap.summary_plot(shap_values, X, plot_type="bar")LIME (Local Interpretable Model-agnostic Explanations): Generates local explanations for a single prediction by fitting a simple, interpretable model (e.g. linear regression) to samples around the data point. Helps users understand how the black box behaves in a particular region.import limeimport lime.lime_tabularexplainer = lime.lime_tabular.LimeTabularExplainer(X, mode="classification") explanation = explainer.explain_instance(X[i], rf_model.predict_proba)explanation.show_in_notebook()For a credit model declining a loan, SHAP and LIME can surface insights like: "The top factors behind this rejection were (1) high debt-to-income ratio (2) multiple recent delinquencies (3) insufficient length of credit history." Armed with this info, the lender could provide the applicant with clearer guidance on how to improve their standing while also demonstrating model fairness to auditors.Case Studies: Putting XAI to WorkAs adoption of AI in lending accelerates,

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Feel disingenuous. Speaking with Polygon, he said that “having a dad bod Necro or an emaciated Druid didn’t really play into the class fantasy,” and the question I might throw back at him is: Why not?To answer this, I want to shift gears away from Diablo for a moment, and look at another game, one that was released a mere four days before. Street Fighter 6 includes a “World Tour” mode, a sort of fighter/brawler/RPG hybrid where you create a custom avatar and bring them into the SF6 universe. Your character is a newbie fighter who, over the course of the World Tour story, learns the fighting styles and techniques of SF6’s various playable characters — some new, and some familiar series regulars.The character creation mode is impressively robust, and in a relative rarity for this industry, you can absolutely make a fat hero for World Tour. I attempted to make as best an approximation of myself as I could, something which — as a fat person in real life — often falls apart entirely, but surprisingly, I really liked the result I got in SF6. Sure, this is still a little idealized (my gams are not nearly this gorgeous), but it’s close enough for a video game.Image: Capcom via Todd Harper for PolygonImage: Capcom via Todd Harper for PolygonImage: Capcom via Todd Harper for PolygonImage: Capcom via Todd Harper for PolygonMore importantly, though, I spent most of World Tour with my character using Chun-Li’s style. This meant my fat ass was jumping off walls, doing ridiculous high kicks, throwing fireballs… all sorts of amazing fighting game chicanery. The game never once said, “Well, you’re fat, so you can learn from E. Honda or Zangief and that’s it.” Anything that a thinner or smaller avatar could do in SF6, my