MATH2319_Phase1
s3686502 Dan Enoka
2 April 2018
——— Standard Approach —– Phase 1 ——-
This dataset is Obtained from and is also available from the UCI machine learning repository,
http://rpubs.com/fast_Eddie/376256 <– saved to and viewable at
Objective: Use machine learning to determine which physiochemical
properties make a wine ‘good’!
For Phase 1 , Regression Analysis will be used.
For phase 2 , Machine Learning will used.
And then one will used to compare against the other.
Definition of physiochemical: (of or pertaining to both physical and chemical properties, changes, and reactions. of or according to physical chemistry.)
Wine Quality in this data set is classified as being, if
equal to “6” = Good , equal to “7” = Good Plus ,
if equal to “8” = Very Good.
The highest value in this data set is “8”
Please Note: Acknowledgements are at the End of this Presentation.
Content: (Or Name per each Column) For more information, read [Cortez et al., 2009]. Input variables (based on physicochemical tests): 1 - fixed acidity 2 - volatile acidity 3 - citric acid 4 - residual sugar 5 - chlorides 6 - free sulfur dioxide 7 - total sulfur dioxide 8 - density 9 - pH 10 - sulphates 11 - alcohol Output variable (based on sensory data): 12 - quality (score between 0 and 10)
What follows is a chance to come to an understanding of the data,
and hopefully, of how each column relates to one another.
## fixed.acidity volatile.acidity citric.acid residual.sugar
## Min. : 4.60 Min. :0.1200 Min. :0.000 Min. : 0.900
## 1st Qu.: 7.10 1st Qu.:0.3900 1st Qu.:0.090 1st Qu.: 1.900
## Median : 7.90 Median :0.5200 Median :0.260 Median : 2.200
## Mean : 8.32 Mean :0.5278 Mean :0.271 Mean : 2.539
## 3rd Qu.: 9.20 3rd Qu.:0.6400 3rd Qu.:0.420 3rd Qu.: 2.600
## Max. :15.90 Max. :1.5800 Max. :1.000 Max. :15.500
## chlorides free.sulfur.dioxide total.sulfur.dioxide
## Min. :0.01200 Min. : 1.00 Min. : 6.00
## 1st Qu.:0.07000 1st Qu.: 7.00 1st Qu.: 22.00
## Median :0.07900 Median :14.00 Median : 38.00
## Mean :0.08747 Mean :15.87 Mean : 46.47
## 3rd Qu.:0.09000 3rd Qu.:21.00 3rd Qu.: 62.00
## Max. :0.61100 Max. :72.00 Max. :289.00
## density pH sulphates alcohol
## Min. :0.9901 Min. :2.740 Min. :0.3300 Min. : 8.40
## 1st Qu.:0.9956 1st Qu.:3.210 1st Qu.:0.5500 1st Qu.: 9.50
## Median :0.9968 Median :3.310 Median :0.6200 Median :10.20
## Mean :0.9967 Mean :3.311 Mean :0.6581 Mean :10.42
## 3rd Qu.:0.9978 3rd Qu.:3.400 3rd Qu.:0.7300 3rd Qu.:11.10
## Max. :1.0037 Max. :4.010 Max. :2.0000 Max. :14.90
## quality
## Min. :3.000
## 1st Qu.:5.000
## Median :6.000
## Mean :5.636
## 3rd Qu.:6.000
## Max. :8.000This following Plot function gives a more generalised overview of all columns
## NULLThis next function shows all correlations of all columns against any particular column of the data set
## With both (Total and Free) Dioxide’s removed
## The three I think are worth looking closer at with relation to Quality
## The following objects are masked _by_ .GlobalEnv:
##
## alcohol, quality## The following objects are masked from Wine (pos = 3):
##
## alcohol, chlorides, citric.acid, density, fixed.acidity,
## free.sulfur.dioxide, pH, quality, residual.sugar, sulphates,
## total.sulfur.dioxide, volatile.acidity
## # A tibble: 11 x 2
## rowname quality
## <chr> <dbl>
## 1 fixed.acidity 0.124
## 2 volatile.acidity -0.391
## 3 citric.acid 0.226
## 4 residual.sugar 0.0137
## 5 chlorides -0.129
## 6 free.sulfur.dioxide -0.0507
## 7 total.sulfur.dioxide -0.185
## 8 density -0.175
## 9 pH -0.0577
## 10 sulphates 0.251
## 11 alcohol 0.476This section below (fit) is for testing the Regression Equation.
The simulator selects random inputs for the Regression Equation an then tries
to validate against the Actual Data for the Regression Model.
I want to see if Machine Learninig can be a better way of predicting
in my case a " better wine " from the various components used to make a wine .
I intend to use this simulator to compare against the Machine Learning model.
I simply want to know if one is better for my Wine prediction than the other.
##
## Call:
## lm(formula = quality ~ fixed.acidity + volatile.acidity + citric.acid +
## residual.sugar + chlorides + free.sulfur.dioxide + total.sulfur.dioxide +
## density + pH + sulphates + alcohol, data = Wine)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.68911 -0.36652 -0.04699 0.45202 2.02498
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.197e+01 2.119e+01 1.036 0.3002
## fixed.acidity 2.499e-02 2.595e-02 0.963 0.3357
## volatile.acidity -1.084e+00 1.211e-01 -8.948 < 2e-16 ***
## citric.acid -1.826e-01 1.472e-01 -1.240 0.2150
## residual.sugar 1.633e-02 1.500e-02 1.089 0.2765
## chlorides -1.874e+00 4.193e-01 -4.470 8.37e-06 ***
## free.sulfur.dioxide 4.361e-03 2.171e-03 2.009 0.0447 *
## total.sulfur.dioxide -3.265e-03 7.287e-04 -4.480 8.00e-06 ***
## density -1.788e+01 2.163e+01 -0.827 0.4086
## pH -4.137e-01 1.916e-01 -2.159 0.0310 *
## sulphates 9.163e-01 1.143e-01 8.014 2.13e-15 ***
## alcohol 2.762e-01 2.648e-02 10.429 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.648 on 1587 degrees of freedom
## Multiple R-squared: 0.3606, Adjusted R-squared: 0.3561
## F-statistic: 81.35 on 11 and 1587 DF, p-value: < 2.2e-16## [1] 5## [1] 5## Regression Value = Data Value
## 2.5 % 97.5 %
## (Intercept) -1.960710e+01 63.537517845
## fixed.acidity -2.590639e-02 0.075887499
## volatile.acidity -1.321126e+00 -0.846054953
## citric.acid -4.712441e-01 0.106116245
## residual.sugar -1.309474e-02 0.045757280
## chlorides -2.696632e+00 -1.051817956
## free.sulfur.dioxide 1.024314e-04 0.008620235
## total.sulfur.dioxide -4.693951e-03 -0.001835208
## density -6.031362e+01 24.551294539
## pH -7.894637e-01 -0.037842600
## sulphates 6.920661e-01 1.140602768
## alcohol 2.242512e-01 0.328144192## Analysis of Variance Table
##
## Response: quality
## Df Sum Sq Mean Sq F value Pr(>F)
## fixed.acidity 1 16.04 16.038 38.1924 8.132e-10 ***
## volatile.acidity 1 143.57 143.573 341.9062 < 2.2e-16 ***
## citric.acid 1 0.02 0.024 0.0581 0.809535
## residual.sugar 1 0.16 0.158 0.3764 0.539600
## chlorides 1 13.06 13.062 31.1057 2.868e-08 ***
## free.sulfur.dioxide 1 2.97 2.974 7.0828 0.007861 **
## total.sulfur.dioxide 1 30.09 30.093 71.6631 < 2.2e-16 ***
## density 1 61.31 61.310 146.0054 < 2.2e-16 ***
## pH 1 7.15 7.154 17.0358 3.859e-05 ***
## sulphates 1 55.70 55.697 132.6366 < 2.2e-16 ***
## alcohol 1 45.67 45.672 108.7643 < 2.2e-16 ***
## Residuals 1587 666.41 0.420
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## (Intercept) fixed.acidity volatile.acidity
## (Intercept) 4.492100e+02 4.253152e-01 3.303414e-01
## fixed.acidity 4.253152e-01 6.733247e-04 -1.562945e-04
## volatile.acidity 3.303414e-01 -1.562945e-04 1.466552e-02
## citric.acid 3.235398e-02 -1.272831e-03 9.543695e-03
## residual.sugar 1.893780e-01 1.677641e-04 4.364326e-05
## chlorides 7.606468e-01 2.538893e-03 -1.340534e-02
## free.sulfur.dioxide -3.813607e-03 -6.205116e-06 4.347546e-05
## total.sulfur.dioxide 1.103784e-03 4.381638e-06 -1.889492e-05
## density -4.583128e+02 -4.409095e-01 -3.364363e-01
## pH 2.234170e+00 3.572150e-03 -6.183079e-04
## sulphates 5.983606e-01 4.511465e-04 2.899835e-03
## alcohol -4.258940e-01 -3.734381e-04 -2.530845e-04
## citric.acid residual.sugar chlorides
## (Intercept) 3.235398e-02 1.893780e-01 7.606468e-01
## fixed.acidity -1.272831e-03 1.677641e-04 2.538893e-03
## volatile.acidity 9.543695e-03 4.364326e-05 -1.340534e-02
## citric.acid 2.166083e-02 -1.179444e-04 -1.627310e-02
## residual.sugar -1.179444e-04 2.250629e-04 6.822396e-05
## chlorides -1.627310e-02 6.822396e-05 1.757984e-01
## free.sulfur.dioxide 5.192585e-05 -4.120402e-06 -5.328066e-05
## total.sulfur.dioxide -2.841887e-05 -3.968613e-07 4.283090e-05
## density -2.737179e-02 -1.931659e-01 -8.508338e-01
## pH 9.654568e-04 9.458076e-04 1.856139e-02
## sulphates -4.468331e-04 3.443137e-04 -1.680336e-02
## alcohol -5.825858e-04 -1.994800e-04 1.025390e-03
## free.sulfur.dioxide total.sulfur.dioxide
## (Intercept) -3.813607e-03 1.103784e-03
## fixed.acidity -6.205116e-06 4.381638e-06
## volatile.acidity 4.347546e-05 -1.889492e-05
## citric.acid 5.192585e-05 -2.841887e-05
## residual.sugar -4.120402e-06 -3.968613e-07
## chlorides -5.328066e-05 4.283090e-05
## free.sulfur.dioxide 4.714508e-06 -1.048949e-06
## total.sulfur.dioxide -1.048949e-06 5.310452e-07
## density 4.013057e-03 -1.241979e-03
## pH -5.726739e-05 2.707286e-05
## sulphates -1.339587e-05 -2.754751e-06
## alcohol 1.503270e-06 1.610225e-06
## density pH sulphates
## (Intercept) -4.583128e+02 2.234170e+00 5.983606e-01
## fixed.acidity -4.409095e-01 3.572150e-03 4.511465e-04
## volatile.acidity -3.364363e-01 -6.183079e-04 2.899835e-03
## citric.acid -2.737179e-02 9.654568e-04 -4.468331e-04
## residual.sugar -1.931659e-01 9.458076e-04 3.443137e-04
## chlorides -8.508338e-01 1.856139e-02 -1.680336e-02
## free.sulfur.dioxide 4.013057e-03 -5.726739e-05 -1.339587e-05
## total.sulfur.dioxide -1.241979e-03 2.707286e-05 -2.754751e-06
## density 4.679910e+02 -2.371814e+00 -6.134005e-01
## pH -2.371814e+00 3.670955e-02 2.817249e-03
## sulphates -6.134005e-01 2.817249e-03 1.307306e-02
## alcohol 4.330216e-01 -2.638799e-03 -8.744756e-04
## alcohol
## (Intercept) -4.258940e-01
## fixed.acidity -3.734381e-04
## volatile.acidity -2.530845e-04
## citric.acid -5.825858e-04
## residual.sugar -1.994800e-04
## chlorides 1.025390e-03
## free.sulfur.dioxide 1.503270e-06
## total.sulfur.dioxide 1.610225e-06
## density 4.330216e-01
## pH -2.638799e-03
## sulphates -8.744756e-04
## alcohol 7.013803e-04—– Machine Learning —— Phase 2 ——–
## name type na mean disp median mad min max
## 1 fixed.acidity character 0 NA 0.9581119 NA NA 1 134
## 2 volatile.acidity character 0 NA 0.9706158 NA NA 1 94
## 3 citric.acid character 0 NA 0.9174742 NA NA 1 264
## 4 residual.sugar character 0 NA 0.9024695 NA NA 1 312
## 5 chlorides character 0 NA 0.9587371 NA NA 1 132
## 6 free.sulfur.dioxide character 0 NA 0.9137230 NA NA 1 276
## 7 total.sulfur.dioxide character 0 NA 0.9731166 NA NA 1 86
## 8 density character 0 NA 0.9774930 NA NA 1 72
## 9 pH character 0 NA 0.9643639 NA NA 1 114
## 10 sulphates character 0 NA 0.9568615 NA NA 1 138
## 11 alcohol character 0 NA 0.9130978 NA NA 1 278
## 12 quality character 0 NA 0.5742420 NA NA 1 1362
## nlevs
## 1 97
## 2 144
## 3 81
## 4 92
## 5 154
## 6 61
## 7 145
## 8 437
## 9 90
## 10 97
## 11 66
## 12 7## 'data.frame': 3199 obs. of 12 variables:
## $ fixed.acidity : chr "fixed acidity" "7.4" "7.8" "7.8" ...
## $ volatile.acidity : chr "volatile acidity" "0.7" "0.88" "0.76" ...
## $ citric.acid : chr "citric acid" "0" "0" "0.04" ...
## $ residual.sugar : chr "residual sugar" "1.9" "2.6" "2.3" ...
## $ chlorides : chr "chlorides" "0.076" "0.098" "0.092" ...
## $ free.sulfur.dioxide : chr "free sulfur dioxide" "11" "25" "15" ...
## $ total.sulfur.dioxide: chr "total sulfur dioxide" "34" "67" "54" ...
## $ density : chr "density" "0.9978" "0.9968" "0.997" ...
## $ pH : chr "pH" "3.51" "3.2" "3.26" ...
## $ sulphates : chr "sulphates" "0.56" "0.68" "0.65" ...
## $ alcohol : chr "alcohol" "9.4" "9.8" "9.8" ...
## $ quality : chr "quality" "5" "5" "5" ...