ML model Hangman

Job Description:


When a user plays Hangman, the server first selects a secret word at random from a list. The server then returns a row of underscores (space separated)—one for each letter in the secret word—and asks the user to guess a letter. If the user guesses a letter that is in the word, the word is redisplayed with all instances of that letter shown in the correct positions, along with any letters correctly guessed on previous turns. If the letter does not appear in the word, the user is charged with an incorrect guess. The user keeps guessing letters until either (1) the user has correctly guessed all the letters in the word or (2) the user has made six incorrect guesses.

You are required to write a "guess" function that takes current word (with underscores) as input and returns a guess letter. You will use the API codes below to play 1,000 Hangman games. You have the opportunity to practice before you want to start recording your game results.

Your algorithm is permitted to use a training set of approximately 250,000 dictionary words. Your algorithm will be tested on an entirely disjoint set of 250,000 dictionary words. Please note that this means the words that you will ultimately be tested on do NOT appear in the dictionary that you are given. You are not permitted to use any dictionary other than the training dictionary we provided. This requirement will be strictly enforced by code review.

You are provided with a basic, working algorithm. This algorithm will match the provided masked string (e.g. a _ _ l e) to all possible words in the dictionary, tabulate the frequency of letters appearing in these possible words, and then guess the letter with the highest frequency of appearence that has not already been guessed. If there are no remaining words that match then it will default back to the character frequency distribution of the entire dictionary.

This benchmark strategy is successful approximately 18% of the time. Your task is to design an algorithm that significantly outperforms this benchmark.

Aptitudini: Machine Learning (ML), Python

Despre client:
( 0 recenzii ) Gurgaon, India

ID Proiect: #35863677

5 freelanceri licitează în medie 4520₹ pentru acest proiect


Hi, I’ve worked on hangman game before also. I can surely code on this. But please reply if you accept my budget, because it’s not that easy to code

%bids___i_sum_sub_35%%project_currencyDetails_sign_sub_36% INR în 3 zile
(25 recenzii)

Hello, I am very familiarized with the requirements of your projects. And it can be done really fast. Let's connect over chat to discuss more on this. Thanks

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(4 recenzii)

Hi, I am a Python developer with around 2 years of experience and I have decent understranding of Artificial Intelligence. I have some ideas on how to develop a machine learning algorithm for the Hangman game and I wou Mai multe

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(1 părere)

One approach to improve the performance of the algorithm would be to prioritize certain letters based on their position in the word. For example, if the letter "e" appears most frequently in the possible words but is a Mai multe

%bids___i_sum_sub_35%%project_currencyDetails_sign_sub_36% INR în 7 zile
(0 recenzii)

HhI I am experienced in and I can start right now but i have few doubts and questions lets have a quick chat and get it started waiting for your replyyy

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(0 recenzii)