Machine Learning $($Regression Models$)$

Instructions: Write step$-$by$-$step Python code to perform all data preparation you may consider relevant for the given dataset; you must perform:

$-$ An overview of the dataset.

$-1$ method for data inputting and$/$or removal of missing values

$-$ Data transformation: $1$ method for numeric variables and$/$or $1$ method for categorical variables.

$-$ Exploratory data analysis: In your report you should describe your more interesting findings.

$*$ For the univariate analysis include only $3$ variables.

$*$ For bivariate or multivariate analysis include only $3$ plots

$*$ Explain the rationale for each of your selections.

$-$Preliminary conclusions and insights derived from your EDA.

$-$Refine your ML model using R$2$ as evaluation metric; you mst deliver:

$-$The JPYNB script containing ONLY ONE model $($with the best result$)$

Notes:

$>$sample$\_$test.csv$$ can only be used for data preprocessing and testing purposes $($NOT training$).$

$>$NO tune parameter optimization will be allowed during

$>$The training process will be allowed using the $$AssignmentI$\_$data.csv$$ file and with the same train$/$test split proportion employed during your research.

Note $1$: The $$sample$\_$test.csv$$ file is a small sample of the $$AssignmentI$\_$data.csv$$ file. Do not draw any conclusions regarding the performance of your model using this dataset.

Note $2$: The independent set to be used for the contest consists of $1163$ rows.

Objective:

To predict the next$-$day temperature according to the given conditi

ons, using a machine learning model $($regression problem$).$ Note: It is NOT a time$-$series problem.

Dataset Description:

The dataset is composed of several next$-$day forecast variables, maximum and minimum temperatures of present$-$day, and geographic auxiliary variables collected for a period of $5$ years by the Korean Meteorological Service over Seoul, South Korea. The output variable is the next$-$day average temperature $($NextDayAvTemp$).$

Datafiles description:

$***$ "AssignmentI$\_$data": csv file $/6588$ rows $($headers included$)$

$***$ "sample$\_$test": csv file $/116$ rows $($headers included$)$

Dataset Variables:

$1.$ Station: Used weather station number.

$2.$ Present$\_$Tmax : Maximum air temperature between $0$ ansample$\_$testod $21$ h on the present day $(\backslash$deg C$).$

$3.$ Present$\_$Tmin: Minimum air temperature between $0$ and $21$ h on the present day $(\backslash$deg C$).$

$4.$ NextDayPred$\_$RHmin: Forecast of next$-$day minimum relative humidity $(\%).5.$NextDayPred $\_$RHmax: Forecast of next$-$day maximum relative humidity $(\%)$

$6.$ NextDayPred $\_$Tmax$\_$lapse: Forecast of next$-$day maximum air temperature applied lapse rate $(\backslash$deg C$)$

$7.$ NextDayPred $\_$Tmin$\_$lapse: Forecast of next$-$day minimum air temperature applied lapse rate $(\backslash$deg C$)$

$8.$NextDayPred $\_$WS: Forecast of next$-$day average wind speed $($m$/$s$)$

$9.$ NextDayPred $\_$LH: Forecast of next$-$day average latent heat flux $($W$/$m$2)$

$10.$ NextDayPred $\_$CC$1$: Forecast of next$-$day $1$st $6-$hour split average cloud cover $(0-5$ h$)(\%).$

$11.$ NextDayPred $\_$CC$2$: Forecast of next$-$day $2$nd $6-$hour split average cloud cover $(6-11$ h$)(\%).$

$12.$ NextDayPred $\_$CC$3$: Forecast of next$-$day $3$rd $6-$hour split average cloud cover $(12-17$ h$)(\%).$

$13.$ NextDayPred $\_$CC$4$: Forecast of next$-$day $4$th $6-$hour split average cloud cover $(18-23$ h$)(\%).$

$14.$ NextDayPred $\_$PPT$1$: Forecast of next$-$day $1$st $6-$hour split average precipitation $(0-5$ h$)(\%).$

$15.$ NextDayPred $\_$PPT$2$: Forecast of next$-$day $2$nd $6-$hour split average precipitation $(6-11$ h$)(\%).$

$16.$ NextDayPred $\_$PPT$3$: Forecast of next$-$day $3$rd $6-$hour split average precipitation $(12-17$ h$)(\%).$

$17.$ NextDayPred $\_$PPT$4$: Forecast of next$-$day $4$th $6-$hour split average precipitation $(18-23$ h$)(\%).$

$18.$ Lat: Latitude $(\backslash$deg $).$

$19.$ Lon: Longitude $(\backslash$deg $).$

$20.$ DEM: Elevation $($m$).$

$21.$ Slope: Slope $(\backslash$deg $).$

$22.$ Solar radiation: Daily incoming solar radiation $($wh$/$m$2).$

$23.$ NextDayAvTemp: The next$-$day average air temperature $(\backslash$deg C$).$