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cacao_flavor

cacao_flavor

active ARFF CC0 Public Domaine Visibility: public Uploaded 13-09-2019 by Sharon
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Chocolate Bar Ratings. Expert ratings of over 1,700 chocolate bars. Each chocolate is evaluated from a combination of both objective qualities and subjective interpretation. A rating here only represents an experience with one bar from one batch. Batch numbers, vintages and review dates are included in the database when known. The database is narrowly focused on plain dark chocolate with an aim of appreciating the flavors of the cacao when made into chocolate. The ratings do not reflect health benefits, social missions, or organic status. Flavor is the most important component of the Flavors of Cacao ratings. Diversity, balance, intensity and purity of flavors are all considered. It is possible for a straight forward single note chocolate to rate as high as a complex flavor profile that changes throughout. Genetics, terroir, post harvest techniques, processing and storage can all be discussed when considering the flavor component. Texture has a great impact on the overall experience and it is also possible for texture related issues to impact flavor. It is a good way to evaluate the makers vision, attention to detail and level of proficiency. Aftermelt is the experience after the chocolate has melted. Higher quality chocolate will linger and be long lasting and enjoyable. Since the aftermelt is the last impression you get from the chocolate, it receives equal importance in the overall rating. Overall Opinion is really where the ratings reflect a subjective opinion. Ideally it is my evaluation of whether or not the components above worked together and an opinion on the flavor development, character and style. It is also here where each chocolate can usually be summarized by the most prominent impressions that you would remember about each chocolate. Flavors of Cacao Rating System: 5= Elite (Transcending beyond the ordinary limits) 4= Premium (Superior flavor development, character and style) 3= Satisfactory(3.0) to praiseworthy(3.75) (well made with special qualities) 2= Disappointing (Passable but contains at least one significant flaw) 1= Unpleasant (mostly unpalatable) Acknowledgements These ratings were compiled by Brady Brelinski, Founding Member of the Manhattan Chocolate Society. For up-to-date information, as well as additional content (including interviews with craft chocolate makers), please see his website: http://flavorsofcacao.com/index.html

9 features

bean_type (target)string41 unique values
1 missing
company__(maker-if_known)string416 unique values
0 missing
specific_bean_origin_or_bar_namestring1039 unique values
0 missing
refnumeric440 unique values
0 missing
review_datenumeric12 unique values
0 missing
cocoa_percentstring45 unique values
0 missing
company_locationstring60 unique values
0 missing
ratingnumeric13 unique values
0 missing
broad_bean_originstring100 unique values
0 missing

62 properties

1795
Number of instances (rows) of the dataset.
9
Number of attributes (columns) of the dataset.
42
Number of distinct values of the target attribute (if it is nominal).
1
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
3
Number of numeric attributes.
0
Number of nominal attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0.01
Percentage of missing values.
33.33
Percentage of numeric attributes.
0
Percentage of nominal attributes.
First quartile of entropy among attributes.
-1.14
First quartile of kurtosis among attributes of the numeric type.
3.19
First quartile of means among attributes of the numeric type.
Standard deviation of the number of distinct values among attributes of the nominal type.
-0.58
First quartile of skewness among attributes of the numeric type.
0.48
First quartile of standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
-0.75
Second quartile (Median) of kurtosis among attributes of the numeric type.
1035.9
Second quartile (Median) of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
-0.53
Second quartile (Median) of skewness among attributes of the numeric type.
2.93
Second quartile (Median) of standard deviation of attributes of the numeric type.
Third quartile of entropy among attributes.
1.13
Third quartile of kurtosis among attributes of the numeric type.
2012.33
Third quartile of means among attributes of the numeric type.
Third quartile of mutual information between the nominal attributes and the target attribute.
-0.14
Third quartile of skewness among attributes of the numeric type.
552.89
Third quartile of standard deviation of attributes of the numeric type.
1
Average class difference between consecutive instances.
1017.14
Mean of means among attributes of the numeric type.
Entropy of the target attribute values.
0.01
Number of attributes divided by the number of instances.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
49.42
Percentage of instances belonging to the most frequent class.
887
Number of instances belonging to the most frequent class.
Maximum entropy among attributes.
1.13
Maximum kurtosis among attributes of the numeric type.
2012.33
Maximum of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
The maximum number of distinct values among attributes of the nominal type.
-0.14
Maximum skewness among attributes of the numeric type.
552.89
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
-0.25
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
Average mutual information between the nominal attributes and the target attribute.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Average number of distinct values among the attributes of the nominal type.
-0.42
Mean skewness among attributes of the numeric type.
185.43
Mean standard deviation of attributes of the numeric type.
Minimal entropy among attributes.
-1.14
Minimum kurtosis among attributes of the numeric type.
3.19
Minimum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
The minimal number of distinct values among attributes of the nominal type.
-0.58
Minimum skewness among attributes of the numeric type.
0.48
Minimum standard deviation of attributes of the numeric type.
0.06
Percentage of instances belonging to the least frequent class.
1
Number of instances belonging to the least frequent class.

8 tasks

0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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