July 25, 2019
Size-normalized examples from the MNIST database. The database used to train and test the systems described in this paper was constructed from the NIST's Special Database 3 and Special Database 1 containing binary images of handwritten digits. NIST originally designated SD-3 as their training set and SD-1 as their test set. However, SD-3 is much cleaner and easier to recognize than SD-1. The reason for this can be found on the fact that SD-3 was collected among Census Bureau employees, while SD-1 was collected among high-school students. Drawing sensible conclusions from learning experiments requires that the result be independent of the choice of training set and test among the complete set of samples. Therefore it was necessary to build a new database by mixing NIST's datasets. SD-1 contains 58,527 digit images written by 500 different writers. In contrast to SD-3, where blocks of data from each writer appeared in sequence, the data in SD-1 is scrambled. Writer identities for SD-1 are available and we used this information to unscramble the writers. We then split SD-1 in two: characters written by the first 250 writers went into our new training set. The remaining 250 writers were placed in our test set. Thus we had two sets with nearly 30,000 examples each. The new training set was completed with enough examples from SD-3, starting at pattern # 0, to make a full set of 60,000 training patterns. Similarly, the new test set was completed with SD-3 examples starting at pattern # 35,000 to make a full set with 60,000 test patterns. In the experiments described here, we only used a subset of 10,000 test images (5,000 from SD-1 and 5,000 from SD-3), but we used the full 60,000 training samples. The resulting database was called the Modified NIST, or MNIST, dataset.
Source: LeCun, Yann, et al. "Gradient-based learning applied to document recognition." Proceedings of the IEEE 86.11 (1998) 2278-2324.
Tags: Boerhaave | COGWEB | Chinese | LSTM | Leiden | PGM | RNN | Ruysch | actors | aesthesis | agency | algorithm | analysis | anatomical | anatomy | androgynous | architecture | archive | artificialia | axis | black-box | body | botanical | brain | categories | categorization | channel | character recognition | chinese | classification | clustering | cnn | codes | cognition | collecting | collection | collections | colonialism | commodification | concept | conceptual-clustering | convolutional neural network | cost | counting | cut | cuts | cutting | datasets | demonstration | diagram | dimensionality | disgust | dissection | distance | domestication | elegance | epistemology | error | euclidean | evaluation | eye | figures | finger | forecasting | forensics | frame | freakish | geometry | gesture | gestures | gradient descent | graph | graphs | grouping | hacking | hand | hand writing | hands | hands-on | handwriting | hardware | history | human | human body | imagination | imperfect | inscription | instruments | joint | kmeans | knowledge | labeling | landmark | learning | location | machine learning | machines | materiality | meaning | measurement | memory | mnist | model | models | monsters | muscles | mystical | mythological | naturalia | nerves | nervous system | network | networks | neural networks | neural-anatomy | neuron | nonlinearity | observation | offline | online | ontologies | ontology | ontology-building | optimization | orientation | orthogonality | parallel | pca | perception | perceptron | perfection | performance | planes | poetic | position | prediction | preparation | preparations | projection | proportion | proportions | psychology | python | races | representation | representations | rhetoric | rnn | segments | selection | sensory experience | sensory perception | similarity | skeleton | skin | skull | skulls | space | sparseness | spectacle | spectators | speech | standard | statistic-ontology | statistical | statistical-ontology | svm | symbols | tacit | taxonomy | theatre | time-series | timeseries | tools | topological | training | treatise | trial | truth | type | typography | unsupervised | vision | visualization | wellcome | word2vec | writing | zodiac |