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R Programming project

Normalize the feature variable x1 (see the Nota-Bene below).

• Calculate the value of the objective function l(β0,β1).

• Choose a value of the learning rate η (you should try different values).

• Initialize the parameter value and calculate the gradient ∇l(β0,β1).

• Update the parameter value.

• Check whether gradient ascent has converged.

Here, it is much better to look at the convergence of the values of l(β0,β1) than the convergence of the parameters themselves.

• Complete the implementation of gradient ascent.

• Predict the labels for a set of test examples.

I am including the data set [login to view URL] in which you should predict the value of the variable chd (response, coronary heart disease diagnosis) from the feature value ldl (low density lipoprotein cholesterol). You may use the first 100 rows for training and any values in the remaining rows for testing.

Habilidades: Linguagem de Programação R, Estatísticas, Processamento de dados, Análise estatística

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Acerca do Empregador:
( 0 comentários ) Sherbrooke, Canada

ID do Projeto: #31027863

8 freelancers estão ofertando em média $70 nesse trabalho

WycOj

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Gkiprop

Dear employer, I hold master's in statistics and continuing with Ph.D. in applied statistics making me suitable for this job. Am an experienced statistic writer for three years. Besides I am a skilled; R programmers sp Mais

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salehdin1993

Hi, I am Saleh din i have master degree statistics and exprience data analysis, report writing, R, spss, latex,data entry, word, python. If you give me this project I will do very well...  

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josephvictory

Hi, I can assist you in this task on coding using R programming language. I am proficient in building predictive models for classification or regression using both machine learning algorithms and neural networks. I’ll Mais

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dominicnzioka197

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atteeek

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alshival

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