UT的R语言作业,比起上次的A1,这次的作业竟然要求画56张图
使用Data frames去读取数据,然后运算,然后写函数去运算,不能使用index而只能慢慢的去loop,效率低不说,这么大的数据量,卡是必然的。
现在提到了代写服务,肯定很多人都不会觉得陌生,就算是国内也是有着专业代写作业的服务行业的,能够为有需求的学生提供很多的帮助,不过其实代写机构在国外会更获得学生的支持,这是因为国外的学校对于平时的作业要求比较严格,为了获得更高的分数顺利毕业,不少留学生就会让代写机构帮忙完成作业,比较常见的作业代写类型,就是计算机专业了,因为对于留学生来说这个技术对于Machine Learning或者AI的代码编程要求更高,所以找代写机构完成作业会简单轻松很多,那么代写机构的水平,要怎么选择才会比较高?
1、代写机构正规专业
不论是在什么情况下,选择正规合法经营的机构肯定是首要的操作,这也是为了避免自己在找机构的时候,出现上当受骗的现象,造成自己的经济出现损失,带来的影响还是非常大的,所以需要注意很多细节才可以,所以在这样的情况下,代写机构的选择,也要选择在经营方面属于正规合法的类型,这样才可以保证服务进行的时候,不会出现各种问题,也可以减少损失的出现,而且正规合法也是代写机构的合格基础。
2、代写机构编程能力
作业的难度相信很多人都很熟悉,特别是对于AI深度学习或者是人工神经网络这种算法来说,因为要对SVM、Design Tree、线性回归以及编程有很高的要求,可以说作业的完成要求非常高,因此才会带动代写机构的发展,找专业的代写机构,一般都是会有专业的人员帮忙进行作业的完成,因为这类型的作业对专业要求比较高,因此代写机构也要具备专业能力才可以,否则很容易导致作业的完成出现问题,出现低分的评价。
3、代写机构收费情况
现在有非常多的留学生,都很在意作业的完成度,为了保证作业可以顺利的被完成,要进行的相关操作可是非常多的,代写机构也是因为如此才会延伸出来的,在现在发展也很迅速,现在选择代写机构的时候,一定要重视收费情况的合理性,因为代写作业还是比较费精力的,而且对于专业能力要求也高,所以价格方面一般会收取几千元至万元左右的价格,但是比较简单的也只需要几百元价格。
4、代写机构完成速度
大部分人都很在意代写机构的专业能力,也会很关心要具备什么能力,才可以展现出稳定的代写能力,其实专业的代写机构,对于作业完成度、作业完成时间、作业专业性等方面,都是要有一定的能力的,特别是在完成的时间上,一定要做到可以根据客户规定的时间内完成的操作,才可以作为合格专业的代写机构存在,大众在选择的时候,也可以重视完成时间这一点来。
现在找专业的CS代写机构帮忙完成作业的代写,完全不是奇怪的事情了,而且专业性越强的作业,需要代写机构帮忙的几率就会越高,代写就发展很好,需求量还是非常高的,这也可以很好的说明了,这个专业的难度以及专业性要求,才可以增加代写机构的存在。
Requirement
You should write R scripts for predicting future values of a time sequence in this assignment, and use them to observations on numbers of maximum temperatures and deaths.
The datasets is derived from that distributed by the NMMAPS, the U.S. National Morbidity Mortality Air Pollution Study, with some missing temperature values. I have provided the datasets from 2000-12-31 to 1994-01-01 as a csv file on the course web page.
Finishing this assignment should provide more practice in basic R scripts, and on the knowledge of datasets frames and of subscripts that are logical or numeric lists.
We wish to predict the number of the maximum temperature and deaths for every day, based only on datasets before that day, except that when predicting the number of deaths on a day, we may use the maximum temperature for that day, as well as previous days.
You should also write a function called predictions, which makes predicts for all days from some start point to the last day for which datasets is provided. This function should take as its arguments a function to use for predicting, a datasets frame with values that may be used for predicting, the series of values for which predicts are to be made, and the start point for making predicts of this series. It should return a list of predicts for values in the series from the specified start point to the end.
Once you have produced predicts for every day, you should produce plots of the predicts, the actual values, and the errors in the predicts. You should also evaluate how good these predicts were in terms of the average absolute value of the error.
You should write several functions for predicting the value of some variable on a single day.
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All these functions should take as their first arguments a datasets frame, containing variables that may be used in making the predict, and as their second argument a series of past values for the variable being predict (which should have at least one past value, and for some functions should have to have more than one past value). This predicting function should return a predict for the next value in this series. The datasets frame should have at least as many rows as the length of the series plus one (so there should be values for the day for which the predict is being made). The datasets frame may have additional rows, but they should not be looked at when making the predict for this day.
Finally, you should try a more powerful predicting method, in which you first make predicts with some function, and then try to use another function to predict the error in the first method. The idea is that if you can manage to predict the error well, you can get a better predict by just adding the predicted error to the original prediction.
Summary
这次作业竟然写了快400行代码,画了56张图,完全就是个体力活。
关于分析师
LE PHUONG
在此对LE PHUONG对本文所作的贡献表示诚挚感谢,她在山东大学完成了计算机科学与技术专业的硕士学位,专注数据分析、数据可视化、数据采集等。擅长Python、SQL、C/C++、HTML、CSS、VSCode、Linux、Jupyter Notebook。