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sdesabbata committed Dec 5, 2023
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234 changes: 117 additions & 117 deletions docs/301-supervised-learning.md
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Expand Up @@ -206,16 +206,16 @@ ru_logit_model %>%
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.19907 0.12575 -9.536 <2e-16 ***
## density_log 1.77052 0.09706 18.242 <2e-16 ***
## (Intercept) -1.24470 0.12590 -9.887 <2e-16 ***
## density_log 1.77746 0.09694 18.335 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 2063.6 on 1667 degrees of freedom
## Residual deviance: 1605.2 on 1666 degrees of freedom
## AIC: 1609.2
## Null deviance: 2087.1 on 1667 degrees of freedom
## Residual deviance: 1616.8 on 1666 degrees of freedom
## AIC: 1620.8
##
## Number of Fisher Scoring iterations: 4
```
Expand Down Expand Up @@ -269,31 +269,31 @@ caret::confusionMatrix(
##
## Reference
## Prediction rural urban
## rural 66 21
## urban 64 266
##
## Accuracy : 0.7962
## 95% CI : (0.7543, 0.8338)
## No Information Rate : 0.6882
## P-Value [Acc > NIR] : 5.237e-07
##
## Kappa : 0.4777
##
## Mcnemar's Test P-Value : 5.225e-06
##
## Sensitivity : 0.5077
## Specificity : 0.9268
## Pos Pred Value : 0.7586
## Neg Pred Value : 0.8061
## Precision : 0.7586
## Recall : 0.5077
## F1 : 0.6083
## Prevalence : 0.3118
## Detection Rate : 0.1583
## Detection Prevalence : 0.2086
## Balanced Accuracy : 0.7173
##
## 'Positive' Class : rural
## rural 58 17
## urban 57 285
##
## Accuracy : 0.8225
## 95% CI : (0.7824, 0.858)
## No Information Rate : 0.7242
## P-Value [Acc > NIR] : 1.836e-06
##
## Kappa : 0.5021
##
## Mcnemar's Test P-Value : 5.797e-06
##
## Sensitivity : 0.5043
## Specificity : 0.9437
## Pos Pred Value : 0.7733
## Neg Pred Value : 0.8333
## Precision : 0.7733
## Recall : 0.5043
## F1 : 0.6105
## Prevalence : 0.2758
## Detection Rate : 0.1391
## Detection Prevalence : 0.1799
## Balanced Accuracy : 0.7240
##
## 'Positive' Class : rural
##
```

Expand Down Expand Up @@ -397,31 +397,31 @@ caret::confusionMatrix(
##
## Reference
## Prediction rural urban
## rural 58 17
## urban 63 279
##
## Accuracy : 0.8082
## 95% CI : (0.767, 0.8448)
## No Information Rate : 0.7098
## P-Value [Acc > NIR] : 2.813e-06
##
## Kappa : 0.4753
##
## Mcnemar's Test P-Value : 4.875e-07
##
## Sensitivity : 0.4793
## Specificity : 0.9426
## Pos Pred Value : 0.7733
## Neg Pred Value : 0.8158
## Precision : 0.7733
## Recall : 0.4793
## F1 : 0.5918
## Prevalence : 0.2902
## Detection Rate : 0.1391
## Detection Prevalence : 0.1799
## Balanced Accuracy : 0.7110
##
## 'Positive' Class : rural
## rural 70 25
## urban 72 250
##
## Accuracy : 0.7674
## 95% CI : (0.7238, 0.8071)
## No Information Rate : 0.6595
## P-Value [Acc > NIR] : 1.071e-06
##
## Kappa : 0.437
##
## Mcnemar's Test P-Value : 3.003e-06
##
## Sensitivity : 0.4930
## Specificity : 0.9091
## Pos Pred Value : 0.7368
## Neg Pred Value : 0.7764
## Precision : 0.7368
## Recall : 0.4930
## F1 : 0.5907
## Prevalence : 0.3405
## Detection Rate : 0.1679
## Detection Prevalence : 0.2278
## Balanced Accuracy : 0.7010
##
## 'Positive' Class : rural
##
```

Expand Down Expand Up @@ -506,30 +506,30 @@ caret::confusionMatrix(
## Reference
## Prediction rural urban
## rural 0 0
## urban 121 296
##
## Accuracy : 0.7098
## 95% CI : (0.6637, 0.753)
## No Information Rate : 0.7098
## P-Value [Acc > NIR] : 0.5245
##
## Kappa : 0
##
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.0000
## Specificity : 1.0000
## Pos Pred Value : NaN
## Neg Pred Value : 0.7098
## Precision : NA
## Recall : 0.0000
## F1 : NA
## Prevalence : 0.2902
## Detection Rate : 0.0000
## Detection Prevalence : 0.0000
## Balanced Accuracy : 0.5000
##
## 'Positive' Class : rural
## urban 124 293
##
## Accuracy : 0.7026
## 95% CI : (0.6562, 0.7461)
## No Information Rate : 0.7026
## P-Value [Acc > NIR] : 0.5242
##
## Kappa : 0
##
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.0000
## Specificity : 1.0000
## Pos Pred Value : NaN
## Neg Pred Value : 0.7026
## Precision : NA
## Recall : 0.0000
## F1 : NA
## Prevalence : 0.2974
## Detection Rate : 0.0000
## Detection Prevalence : 0.0000
## Balanced Accuracy : 0.5000
##
## 'Positive' Class : rural
##
```

Expand Down Expand Up @@ -583,29 +583,29 @@ caret::confusionMatrix(
##
## Reference
## Prediction rural urban
## rural 43 25
## urban 78 271
## rural 34 28
## urban 90 265
##
## Accuracy : 0.753
## 95% CI : (0.7087, 0.7937)
## No Information Rate : 0.7098
## P-Value [Acc > NIR] : 0.02809
## Accuracy : 0.717
## 95% CI : (0.6712, 0.7598)
## No Information Rate : 0.7026
## P-Value [Acc > NIR] : 0.2795
##
## Kappa : 0.3112
## Kappa : 0.2087
##
## Mcnemar's Test P-Value : 2.996e-07
## Mcnemar's Test P-Value : 1.96e-08
##
## Sensitivity : 0.3554
## Specificity : 0.9155
## Pos Pred Value : 0.6324
## Neg Pred Value : 0.7765
## Precision : 0.6324
## Recall : 0.3554
## F1 : 0.4550
## Prevalence : 0.2902
## Detection Rate : 0.1031
## Detection Prevalence : 0.1631
## Balanced Accuracy : 0.6355
## Sensitivity : 0.27419
## Specificity : 0.90444
## Pos Pred Value : 0.54839
## Neg Pred Value : 0.74648
## Precision : 0.54839
## Recall : 0.27419
## F1 : 0.36559
## Prevalence : 0.29736
## Detection Rate : 0.08153
## Detection Prevalence : 0.14868
## Balanced Accuracy : 0.58932
##
## 'Positive' Class : rural
##
Expand Down Expand Up @@ -719,29 +719,29 @@ caret::confusionMatrix(
##
## Reference
## Prediction rural urban
## rural 52 36
## urban 69 260
## rural 42 30
## urban 82 263
##
## Accuracy : 0.7482
## 95% CI : (0.7037, 0.7892)
## No Information Rate : 0.7098
## P-Value [Acc > NIR] : 0.045773
## Accuracy : 0.7314
## 95% CI : (0.6861, 0.7734)
## No Information Rate : 0.7026
## P-Value [Acc > NIR] : 0.1082
##
## Kappa : 0.3352
## Kappa : 0.2688
##
## Mcnemar's Test P-Value : 0.001791
## Mcnemar's Test P-Value : 1.442e-06
##
## Sensitivity : 0.4298
## Specificity : 0.8784
## Pos Pred Value : 0.5909
## Neg Pred Value : 0.7903
## Precision : 0.5909
## Recall : 0.4298
## F1 : 0.4976
## Prevalence : 0.2902
## Detection Rate : 0.1247
## Detection Prevalence : 0.2110
## Balanced Accuracy : 0.6541
## Sensitivity : 0.3387
## Specificity : 0.8976
## Pos Pred Value : 0.5833
## Neg Pred Value : 0.7623
## Precision : 0.5833
## Recall : 0.3387
## F1 : 0.4286
## Prevalence : 0.2974
## Detection Rate : 0.1007
## Detection Prevalence : 0.1727
## Balanced Accuracy : 0.6182
##
## 'Positive' Class : rural
##
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4 changes: 2 additions & 2 deletions docs/302-unsupervised-learning.md
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Expand Up @@ -55,13 +55,13 @@ library(tidyverse)
```

```
## ── Attaching core tidyverse packages ────────────────────────────────────────────────────────────────────────────────────────── tidyverse 2.0.0 ──
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.3 ✔ readr 2.1.4
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ ggplot2 3.4.3 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.0
## ✔ purrr 1.0.2
## ── Conflicts ──────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
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Expand Up @@ -125,7 +125,7 @@ <h1>Page not found<a class="anchor" aria-label="anchor" href="#page-not-found"><
<footer class="bg-primary text-light mt-5"><div class="container"><div class="row">

<div class="col-12 col-md-6 mt-3">
<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-11-28.</p>
<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-12-05.</p>
</div>

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2 changes: 1 addition & 1 deletion docs/appendix-1.html
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Expand Up @@ -526,7 +526,7 @@ <h3>Factors<a class="anchor" aria-label="anchor" href="#factors"><i class="fas f
<footer class="bg-primary text-light mt-5"><div class="container"><div class="row">

<div class="col-12 col-md-6 mt-3">
<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-11-28.</p>
<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-12-05.</p>
</div>

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2 changes: 1 addition & 1 deletion docs/comparing-data.html
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<footer class="bg-primary text-light mt-5"><div class="container"><div class="row">

<div class="col-12 col-md-6 mt-3">
<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-11-28.</p>
<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-12-05.</p>
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2 changes: 1 addition & 1 deletion docs/data-manipulation.html
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<footer class="bg-primary text-light mt-5"><div class="container"><div class="row">

<div class="col-12 col-md-6 mt-3">
<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-11-28.</p>
<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-12-05.</p>
</div>

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2 changes: 1 addition & 1 deletion docs/exploratory-statistics.html
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<footer class="bg-primary text-light mt-5"><div class="container"><div class="row">

<div class="col-12 col-md-6 mt-3">
<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-11-28.</p>
<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-12-05.</p>
</div>

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2 changes: 1 addition & 1 deletion docs/exploratory-visualisation.html
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<footer class="bg-primary text-light mt-5"><div class="container"><div class="row">

<div class="col-12 col-md-6 mt-3">
<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-11-28.</p>
<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-12-05.</p>
</div>

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Expand Up @@ -367,7 +367,7 @@ <h2>Part 3<a class="anchor" aria-label="anchor" href="#part-3"><i class="fas fa-
<footer class="bg-primary text-light mt-5"><div class="container"><div class="row">

<div class="col-12 col-md-6 mt-3">
<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-11-28.</p>
<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-12-05.</p>
</div>

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Expand Up @@ -257,7 +257,7 @@ <h3>Session info<a class="anchor" aria-label="anchor" href="#session-info"><i cl
<footer class="bg-primary text-light mt-5"><div class="container"><div class="row">

<div class="col-12 col-md-6 mt-3">
<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-11-28.</p>
<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-12-05.</p>
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2 changes: 1 addition & 1 deletion docs/index.md
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---
title: "R for Geographic Data Science"
author: "Stefano De Sabbata"
date: "2023-11-28"
date: "2023-12-05"
site: bookdown::bookdown_site
documentclass: book
bibliography: [references.bib, packages.bib]
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<footer class="bg-primary text-light mt-5"><div class="container"><div class="row">

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<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-11-28.</p>
<p>"<strong>R for Geographic Data Science</strong>" was written by Stefano De Sabbata. It was last built on 2023-12-05.</p>
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