<prompt> Etsa algorithm ho bolela esale pele maraka oa setoko u sebelisa maemo a fanoeng.K. Lenane la boitsebiso le kenyelletsa lintlha tse amanang le matšoao a moruo, joalo ka GDP le likhaello tsa ho hloka mosebetsi, hammoho le lintlha tse ikhethileng tsa khamphani joalo ka meputso, chelete ea maraka, le likhakanyo tsa lichelete. B. Algorithm e lokela ho khona ho bolela esale pele mokhoa oa maraka ka nako ea bonyane khoeli e le ngoe.  <response>: Instruction in English: Design an algorithm to predict the stock market using the given conditions. . Response in English: Algorithm for Predicting the Stock Market1. Collect and Pre-Process Data: a. Firstly, collect the data on economic indicators such as GDP and unemployment rates, and company-specific data such as earnings, market capitalization, and financial ratios. b. Pre-process the data by removing any missing or irrelevant information, and then dividing it into training and testing datasets. 2. Feature Extraction: a. Extract the features or the variables from the dataset that could impact the stock market trend. b. These features could be the companys earnings, financial ratios, and economic indicators such as GDP and unemployment rates. c. Also calculate technical indicators such as moving averages, relative strength index, and others that are relevant to the stock market prediction.3. Choose a Model a. Based on data and the problem, choose a suitable model for prediction. b. Some of the commonly used models for stock market prediction are linear regression, random forest, and neural networks.4. Train the Model: a. Train the chosen model on the training dataset using the extracted features along with their relationship with the stock market trends. b. Evaluate the models performance on the training data and fine-tune it to improve the accuracy of the predictions.5. Make Predictions: a. Use the trained model to make predictions on the testing dataset. b. The model should be able to predict the stock market trend over the next month with reasonable accuracy. 6. Evaluate Performance: a. Evaluate the performance of the model by comparing its predictions with the actual stock market trend. b. If the models performance is satisfactory, it could be used for predicting the stock market trend. If not, the model should be fine-tuned further or a different model could be tried. . Response in Sesotho: Algorithm bakeng sa ho bolela esale pele ka Maraka oa Li-stock 1. Bokella me U Lokisetse Lintlha Pele: a. Taba ea pele, bokella lintlha tse mabapi le matšoao a moruo a joalo ka GDP le sekhahla sa tlhokeho ea mosebetsi, le lintlha tse ikhethileng tsa khamphani joalo ka meputso, chelete ea maraka le likarohano tsa lichelete. b. Hlophisa data esale pele ka ho tlosa tlhahisoleseling efe kapa efe e sieo kapa e sa sebetseng, ebe o e arola ka li-dataset tsa koetliso le liteko. 2. Feature Extraction: a. Hlakola likarolo kapa mefuta e fapaneng ho tsoa ho dataset e ka amang mokhoa oa maraka oa setoko. b. Likarolo tsena e ka ba meputso ea khamphani, likarohano tsa lichelete, le matšoao a moruo joalo ka GDP le litefiso tsa tlhokeho ea mesebetsi. c. Hape bala matšoao a tekheniki joalo ka karolelano e tsamaeang, index ea matla a lekanyelitsoeng, le tse ling tse amanang le ponelopele ea maraka oa setoko. 3. Khetha Mohlala a. Ho itšetlehile ka lintlha le bothata, khetha mohlala o loketseng oa ho bolela esale pele. b. E meng ea mefuta e sebelisoang haholo bakeng sa ho bolela esale pele maraka oa setoko ke ho fokotseha ha mela, meru e sa reroang, le marang-rang a neural. 4. Koetlisa Mohlala: a. Koetlisa mohlala o khethiloeng lethathamong la lithupelo u sebelisa likarolo tse nkiloeng hammoho le kamano ea bona le mekhoa ea maraka oa setoko. b. Lekola tšebetso ea mohlala ho data ea koetliso le ho e lokisa hantle ho ntlafatsa bonnete ba likhakanyo. 5. Etsa Lipolelo-pele: a. Sebelisa mohlala o koetlisitsoeng ho etsa likhakanyo ho dataset ea liteko. b. Mohlala o lokela ho khona ho bolela esale pele mokhoa oa maraka oa lichelete khoeling e tlang ka ho nepahala ho utloahalang. 6. Lekola Tsebetso: a. Lekola tsebetso ea mohlala ka ho bapisa likhakanyo tsa oona le mokhoa oa sebele oa maraka oa lichelete. b. Haeba tsebetso ea mohlala e khotsofatsa, e ka sebelisoa ho bolela esale pele mokhoa oa maraka oa thepa. Haeba ho se joalo, mohlala o lokela ho lokisoa hantle kapa ho lekoa mohlala o fapaneng. 