Curve Number from time series data as well as to plot the CN-P asymptotic behaviour, according to Hawkins (1993). The direct storm runoff can be calulated using the functionDirectStormRunoff()andRegionalisedCN()allows to calculate the CN given soil and vegetation maps of the area. The ...
I want to compare a given classification algorithm with others via the Area under the (ROC-)curve metric. Unfortunately this algorithm only outputs the values of the respective confusion matrix (TP, FP, TN, FN) and a subset of the predicted positives, but no probability score for any...
Then generate a chi-square curve for your results along with a p-value (See: Calculate a chi-square p-value Excel). Small p-values (under 5%) usually indicate that a difference is significant (or “small enough”). Tip: The Chi-square statistic can only be used on numbers. They can...
“Area Under ROC Curve performance of the model X is 0.59, the 95% confidence interval calculated using bootstrapped re-sampling is [0.92-0.96].” I used your codes on my data and this is what I got. What I might be doing wrong? Reply Jason Brownlee August 5, 2021 at 5:25 am ...
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Then compare the models performance though AUC (area under ROC curve) and the procesing time to choose the final model the barplot shows the unbalanced number of observations in credit risk vs non-credit risk people. Therefore, We will use all the observations to create our predictive model an...
land productivity has experienced a positive dynamics during the past two decades in most of this area. Results obtained for intermediate or other time windows showed effects of specific growing conditions, such as droughts, during the end years of the time series. This is similar to other areas...