{"id":2028,"date":"2022-03-28T20:43:45","date_gmt":"2022-03-28T20:43:45","guid":{"rendered":"https:\/\/salarydistribution.com\/machine-learning\/2022\/03\/28\/grading-our-2022-oscars-machine-learning-predictions\/"},"modified":"2022-03-28T20:43:45","modified_gmt":"2022-03-28T20:43:45","slug":"grading-our-2022-oscars-machine-learning-predictions","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2022\/03\/28\/grading-our-2022-oscars-machine-learning-predictions\/","title":{"rendered":"Grading our 2022 Oscars Machine Learning Predictions"},"content":{"rendered":"
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The 94th Academy Awards<\/strong><\/a> ceremony is a wrap and thanks to an unexpected turn of events it seems to have the distinction of being dubbed as the most chaotic of them all<\/a><\/strong>. The night began with all the familiar signs of what one would expect from a non-pandemic Oscars proceedings with the celebrities streaming in, the red carpet interviews, and the inevitable opening salvos from the night\u2019s hosts. But then, suddenly, it took a turn for the worse when Chris Rock took the stage for a serving of his no-holds-barred celebrity jokes, except this time Will Smith responded with a \u201cservice return\u201d of his own<\/strong><\/a> that will perhaps forever be remembered as the defining moment of this year\u2019s Academy Awards. While we hope that tempers will fade in the coming days, we\u2019d like to quietly jump into the movies themselves and how we did with our predictions this year.<\/p>\n

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With modifications to our data and approach, this year\u2019s prediction challenge turned out a fruitful one as we had 15 out of 19 predictions correct<\/strong><\/a> for a pretty decent hit rate of 79%!<\/strong> In fact, we\u2019ve never had 15 right picks before as there were some question marks as to whether some of the more technical categories we chose to add for the first time would prove predictable. Although a single year can be misleading, we have a good reason to continue including the newly added categories going forward. <\/p>\n

As usual, we have to remind ourselves that getting 15 out of 19 right with anywhere between 5 to 10 nominees for each category would be an exercise in futility if we were to engage in the random act of flipping coins instead. Basically, we\u2019re talking about finding the one correct combination out of 30,517,600,000 possible combinations. As the tables below summarize, armed with a spreadsheet full of data, Machine Learning does a remarkable job of almost fully solving this complex puzzle despite having no preconceived notion of what a movie is!<\/strong><\/p>\n

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Analysis and Lessons Learned<\/h2>\n