Latent factors Rotation Variable- factor relationships Centroid stabilize Voting ensemble Weight adaptation Random Forest Overgeneralization Identifiers Within cluster variability Two- Dimensional Map First Principal Component
Age Euclidean Competitive learning Correlated Same evaluation metric Cross Model comparison Shared variance proportion Covariance Matrix Distance ROC Curve Strategy Development Meta- Model Initialization Boosting Neighborhood function Poorly Location Topology Variance Explained Usage Data Linear combinations MAE Spherical Factor structure Log loss Loadings Distort clusters Stacking Uncorrelated Targeting Validation set Error
Bootstrap sampling Scree plot Bagging Latent factors Rotation Variable- factor relationships Centroid stabilize Voting ensemble Weight adaptation Random Forest Overgeneralization Identifiers Within cluster variability Two- Dimensional Map First Principal Component Age Euclidean Competitive learning Correlated Same evaluation metric Cross Model comparison Shared variance proportion Covariance Matrix Distance ROC Curve Strategy Development Meta- Model Initialization Boosting Neighborhood function Poorly Location Topology Variance Explained Usage Data Linear combinations MAE Spherical Factor structure Log loss Loadings Distort clusters Stacking Uncorrelated Targeting Validation set Error Bootstrap sampling Scree plot Bagging
(Print) Use this randomly generated list as your call list when playing the game. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.
F-Latent factors
F-Rotation
F-Variable-factor relationships
K-Centroid stabilize
E-Voting ensemble
S-Weight adaptation
E-Random Forest
S-Overgeneralization
S-Identifiers
K-Within cluster variability
S-Two-Dimensional
S-Map
P-First Principal Component
S-Age
K-Euclidean
S-Competitive learning
F-Correlated
P-Same evaluation metric
P-Cross Model comparison
F-Shared variance proportion
P-Covariance Matrix
S-Distance
P-ROC Curve
S-Strategy Development
E-Meta-Model
K-Initialization
E-Boosting
S-Neighborhood function
K-Poorly
S-Location
S-Topology
P-Variance Explained
S-Usage Data
P-Linear combinations
P-MAE
K-Spherical
F-Factor structure
P-Log loss
P-Loadings
K-Distort clusters
E-Stacking
P-Uncorrelated
S-Targeting
P-Validation set
F-Error
E-Bootstrap sampling
P-Scree plot
E-Bagging