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超级解压代写澳洲QBUS2820 Predictive Analytics考试assignment

今日爆单中,为了单车换摩托,拼了呀!

扫一扫又不会怀孕,扫一扫,作业无烦恼。

一日之计在于晨,最理想的状态就是工作+健身两不误,为了自己的事业和八块腹肌,尽情练起来吧!

选择rise锐泽paper咨询留学,那就跟您的作业coursework等等,好好告个别吧~毕竟很快就会pass这门课,统统加油呀!

加油呀!本节课需要阅读的三本书↓

  1. The Elements of Statistical Learning
  2. An introduction to statistical learning: With applications in R.
  3. Forecasting: principles and practice代写.

• Statistical terminologies are in bold or blue when first introduced, e.g., autoregression, recurrent neural network
• When there are something needed your attention, they are put in italic or red, e.g., This part will be tested in the exam
• This is an applied course – we focus more on applications, explaining how the methods work, how to use them, their advantages and limits, etc. Theoretical part and maths are also sometimes discussed briefly.

Predictive Analytics
Week 7: Advanced regression是最有意思的一个章节了

• We minimise the penalised RSS. The second terms penalises the parameter complexity
• It turns out that the idea of jointly optimising Error term + Model complexity term is very common in Statistics/Data Mining and Machine Learning
• Note that one usually doesn’t penalise the intercept β0
• λ controls the penalty, needs to be selected