Status: Clean dataset ready for modeling

Columns (n=2):

• Claims: Total number of insurance claims

• Payments (Outcome): Total sum of claims (in thousand of Swedish Kronor)

Rows (n=63):

• Individual Swedish Providences

Status: Clean dataset ready for modeling. Contains categorical and numeric variables with interacting variables.

Columns (n=9):

• Sex: (M)ale, (F)emale, (I)nfant

• Length: Measure of longest dimension of shell

• Diameter: Measure perpendicular to the Length measure

• Height: Vertical measure of shell

• Whole Height: Vertical measure of shell and snail

• Shucked Weight: Weight of snail without shell

• Viscera Weight: Snail gut weight

• Shell Weight: Weight of dried shell

• Rings (Outcome): Each ring is approximately 1.5 years of age

Rows (n=4,177):

• Individual Abalone snails

Status: Clean dataset, but has interacting variables and imbalanced Outcomes. Used for multi-class classification or regression modeling.

Columns (n=12):

• Fixed Acidity: Amount of non-volatile acids (does not evaporate). Gives wines a beneficial sour or tart taste.

• Volatile Acidity: Amount of acetic acid. High levels negatively affect wine by giving it a vinegar taste.

• Citric Acid: Can beneficially affect flavors of wine

• Residual Sugar: Amount of sugar remaining after fermentation. Higher levels give wine a sweet taste.

• Chlorides: Amount of salt in wine

• Free Sulfuric Dioxide: Prevents oxidation of wine

• Total Sulfuric Dioxide: At high levels, affects smell and taste of wine

• Density: Molecular density of wine, affected by alcohol and sugar content

• pH: Acidic measure of the wine (0 = Acidic, 7 = neutral, 14 = Basic)

• Sulphates: Added to wine to moderate Sulfur Dioxide levels (Free Sulfuric Dioxide, Total Sulfuric Dioxide)

• Alcohol: Percent of alcohol content in wine

• Quality (Outcome): Judge's score between 0 and 10

Rows (n=4,898):

• Individual wine samples

Status: Clean dataset with balanced Outcomes.

Columns (n=5):

• Variance: Measure of variability in image

• Skewness: Measure of symmetry

• Kurtosis: Measure of 'tailedness' of distribution

• Entropy: Measure of randomness in image

• Authenticity (Outcome): 0 for authentic, 1 for inauthentic

Rows (n=1,372):

• Individually photographed banknotes

Status: Clean dataset with balanced Outcomes.

Columns (n=5):

• Sepal Length: Length of leaf that encases flower bud

• Sepal Width: Width of leaf that encases flower bud

• Petal Length: Average length of petal

• Petal Width: Average width of petal

• Flower (Outcome): Iris Setosa, Iris Versicolour, Iris Virginica

Rows (n=150):

• Individual flower samples