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Ada Boost with boosting stumps

$30-250 USD

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Posted about 9 years ago

$30-250 USD

Paid on delivery
Implement an AdaBoost with boosting stumps (30 points) and apply the algorithm to the breast cancer data set [login to view URL], ID 322391. The data set contains 30 features and asks for a classification of breast tumors into benign and malignant. Plot the classification errors over the iterations and use 5-fold cross-validation to validate your results (70 points). Hint: you need to calculate the average cross-validation errors minus and plus one standard deviation. Decision stumps are often used as components (called ”weak learners” or ”base learners”) in machine learning ensemble techniques such as bagging and boosting. A boosting stump is a machine learning model consisting of a one-level decision tree. That is, it is a decision tree with one internal node (the root) which is immediately connected to the terminal nodes (its leaves). A decision stump makes a prediction based on the value of just a single input feature. Question 2. (100 points) Implement a Bagging with bagging stumps (30 points) and apply the algorithm to the breast cancer data set [login to view URL] Plot the average bootstrap errors plus or minus one standard deviation and compared with those in Adaboost procedure
Project ID: 7325980

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Active 9 yrs ago

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3 freelancers are bidding on average $222 USD for this job
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Hi, I am a quantitative analyst with an reputed equities trading firm. As a part of my everyday work, I develop algorithmic trading strategies. I have ample experience of statistics and machine learning. I am proficient in statistical analysis software like R, MATLAB and Python. I have extensively used the caret package(popular R packages for machine learning). Given my experience and skill set, I would be a perfect fit for the work at hand. I promise to work hard and deliver quality product in time. Looking forward to working with you. Warm regards, Shashwat Malot
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I am a doctoral student at University of Zurich. I am pursuing my PhD in machine learning and statistics. Having an experience of more than 5 year in statistics, I believe that I will be able to deliver the task within the time schedule. I am proficient in R and Matlab. I am already using adaBoost for my data analysis in Matlab and R. Moreover, I have a Kaggle ranking of 1122 out of around 272000 people registered.
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