About the Accuracy Formula and How to Calculate It
The Accuracy Formula helps you determine the amount of error in values measured. The error rate is the difference between what was measured and what was observed. High accuracy is defined as having a low error rate. The Accuracy Formula also provides a percentage value for accuracy. It is calculated so that the total of both accuracy and error rate equals 100 per cent. The Accuracy Formula is one of the most popular formulas to measure measurement accuracy.
There are other terms used in data science to express accuracies, like precision, recall, and F1 Score. But what is the Accuracy Formula, and how do you calculate it? Read on to learn more. Is it necessary? What are the benefits of accurate calculations? Let's look at each one. It will be easier to determine the accuracy of a dataset if it can be classified correctly. Accuracy Formulas are also commonly used in statistics.
The accuracy percentage is the result of the deviation between the actual demand and the forecasted demand. However, there is a risk of a negative deviation in the accuracy percentage if the Demand value is higher than the Forecast value. In such a case, the Accuracy Formula will show a negative accuracy percentage. In this case, the Demand value will be used in the denominator. In this case, the accuracy percentage will be zero. Another type of Accuracy Formula is known as the absolute variance. This formula involves summing the absolute variance of all SKUs in a store. Then, the total value of all SKUs is rounded to the nearest thousand. This formula can be more difficult to calculate than the SKU integrity formula. However, it is the most accurate and useful way to estimate accuracy. If your accuracy is high, you can use the Absolute Variance Formula.
The Accuracy Formula is another useful tool for multiclass classification. The Balanced Accuracy is the average of the Recall score for each class. Although it tends to be similar to the Accuracy formula, it can be used to compare a dataset with a high degree of imbalance. For example, when working with an imbalanced dataset, the F1 score would predict fifteen positive samples but nine hundred true negatives. Balanced Accuracy on the other hand does care about the positives more than the negatives.
Another popular method is the Balanced Accuracy formula. This method makes use of the Balanced Accuracy formula by multiplying the recall by the weight of the class. The weight of the class is the frequency of the class in the entire dataset. In this way, each unit contributes equally to the Accuracy value. In addition, the weight of a class will be proportional to its size. Consequently, a high number of units will result in a higher Accuracy value than a low number of units. Check out the List of Maths Formulas.
The accuracy formula is easy to understand and intuitive. It takes into account the True Positive and True Negative elements of the confusion matrix. It also takes into account all elements of the confusion matrix outside of the main diagonal. Accuracy is the probability that the model will correctly predict the classification. It is also valid for multi-class cases. So, this formula is extremely useful in measuring accuracy. So, what is the Accuracy Formula? Here are some of the most important things to consider.
Accuracy = 100% - Error Rate
Error Rate = |Observed Value - Actual Value|/Actual Value × 100
Solved example based on Accuracy Formula
Example 1: The length of a rectangular box is 1.2 meters, it was measured with tape and the length was measured at 1.22 meters. Find accuracy of measurement.
Solution:
- Given the length of rectangular box = 1.20 meters
- The measured length of the rectangular box = 1.22 meters
- Error Rate=|Measured Value - Given Value|Given Value×100
- =(1.22−1.20)1.20×100
- =0.021.20×100
- =1.67%Error Rate
- =|Measured Value - Given Value|Given Value×100
- =(1.22−1.20)1.20×100
- =0.021.20×100
- =1.67%
- Accuracy = 100% - Error% = 100% - 1.67% = 98.33%
Answer: accuracy is 98.33%
Example 2: Measuring tape can measure with an accuracy of 99.8%. What is the possible range of length that can be obtained by using this measuring tape so to measure cloth of length 2 meters?
Solution:
- Given the accuracy of measuring tape = 99.8%
- Error rate measurement = 100% - 99.8% = 0.2%
- length of the cloth = 2 m
- New measurement using this measuring tape = 2m±0.2%×2m
- =2±0.0042m±0.2%×2m=2±0.004
- Maximum value of measurement =2m + 0.004 = 2.004m
- Minimum value of measurement = 2m - 0.004m = 1.996m
Answer: range of measures that can be obtained is from 1.996m to 2.004m.
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