Update parquet files

.gitattributes

@@ -1,37 +0,0 @@
-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
-*.bz2 filter=lfs diff=lfs merge=lfs -text
-*.ftz filter=lfs diff=lfs merge=lfs -text
-*.gz filter=lfs diff=lfs merge=lfs -text
-*.h5 filter=lfs diff=lfs merge=lfs -text
-*.joblib filter=lfs diff=lfs merge=lfs -text
-*.lfs.* filter=lfs diff=lfs merge=lfs -text
-*.model filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text
-*.onnx filter=lfs diff=lfs merge=lfs -text
-*.ot filter=lfs diff=lfs merge=lfs -text
-*.parquet filter=lfs diff=lfs merge=lfs -text
-*.pb filter=lfs diff=lfs merge=lfs -text
-*.pt filter=lfs diff=lfs merge=lfs -text
-*.pth filter=lfs diff=lfs merge=lfs -text
-*.rar filter=lfs diff=lfs merge=lfs -text
-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
-*.tar.* filter=lfs diff=lfs merge=lfs -text
-*.tflite filter=lfs diff=lfs merge=lfs -text
-*.tgz filter=lfs diff=lfs merge=lfs -text
-*.wasm filter=lfs diff=lfs merge=lfs -text
-*.xz filter=lfs diff=lfs merge=lfs -text
-*.zip filter=lfs diff=lfs merge=lfs -text
-*.zstandard filter=lfs diff=lfs merge=lfs -text
-*tfevents* filter=lfs diff=lfs merge=lfs -text
-# Audio files - uncompressed
-*.pcm filter=lfs diff=lfs merge=lfs -text
-*.sam filter=lfs diff=lfs merge=lfs -text
-*.raw filter=lfs diff=lfs merge=lfs -text
-# Audio files - compressed
-*.aac filter=lfs diff=lfs merge=lfs -text
-*.flac filter=lfs diff=lfs merge=lfs -text
-*.mp3 filter=lfs diff=lfs merge=lfs -text
-*.ogg filter=lfs diff=lfs merge=lfs -text
-*.wav filter=lfs diff=lfs merge=lfs -text

Iris.csv

@@ -1,151 +0,0 @@
-Id,SepalLengthCm,SepalWidthCm,PetalLengthCm,PetalWidthCm,Species
-1,5.1,3.5,1.4,0.2,Iris-setosa
-2,4.9,3.0,1.4,0.2,Iris-setosa
-3,4.7,3.2,1.3,0.2,Iris-setosa
-4,4.6,3.1,1.5,0.2,Iris-setosa
-5,5.0,3.6,1.4,0.2,Iris-setosa
-6,5.4,3.9,1.7,0.4,Iris-setosa
-7,4.6,3.4,1.4,0.3,Iris-setosa
-8,5.0,3.4,1.5,0.2,Iris-setosa
-9,4.4,2.9,1.4,0.2,Iris-setosa
-10,4.9,3.1,1.5,0.1,Iris-setosa
-11,5.4,3.7,1.5,0.2,Iris-setosa
-12,4.8,3.4,1.6,0.2,Iris-setosa
-13,4.8,3.0,1.4,0.1,Iris-setosa
-14,4.3,3.0,1.1,0.1,Iris-setosa
-15,5.8,4.0,1.2,0.2,Iris-setosa
-16,5.7,4.4,1.5,0.4,Iris-setosa
-17,5.4,3.9,1.3,0.4,Iris-setosa
-18,5.1,3.5,1.4,0.3,Iris-setosa
-19,5.7,3.8,1.7,0.3,Iris-setosa
-20,5.1,3.8,1.5,0.3,Iris-setosa
-21,5.4,3.4,1.7,0.2,Iris-setosa
-22,5.1,3.7,1.5,0.4,Iris-setosa
-23,4.6,3.6,1.0,0.2,Iris-setosa
-24,5.1,3.3,1.7,0.5,Iris-setosa
-25,4.8,3.4,1.9,0.2,Iris-setosa
-26,5.0,3.0,1.6,0.2,Iris-setosa
-27,5.0,3.4,1.6,0.4,Iris-setosa
-28,5.2,3.5,1.5,0.2,Iris-setosa
-29,5.2,3.4,1.4,0.2,Iris-setosa
-30,4.7,3.2,1.6,0.2,Iris-setosa
-31,4.8,3.1,1.6,0.2,Iris-setosa
-32,5.4,3.4,1.5,0.4,Iris-setosa
-33,5.2,4.1,1.5,0.1,Iris-setosa
-34,5.5,4.2,1.4,0.2,Iris-setosa
-35,4.9,3.1,1.5,0.1,Iris-setosa
-36,5.0,3.2,1.2,0.2,Iris-setosa
-37,5.5,3.5,1.3,0.2,Iris-setosa
-38,4.9,3.1,1.5,0.1,Iris-setosa
-39,4.4,3.0,1.3,0.2,Iris-setosa
-40,5.1,3.4,1.5,0.2,Iris-setosa
-41,5.0,3.5,1.3,0.3,Iris-setosa
-42,4.5,2.3,1.3,0.3,Iris-setosa
-43,4.4,3.2,1.3,0.2,Iris-setosa
-44,5.0,3.5,1.6,0.6,Iris-setosa
-45,5.1,3.8,1.9,0.4,Iris-setosa
-46,4.8,3.0,1.4,0.3,Iris-setosa
-47,5.1,3.8,1.6,0.2,Iris-setosa
-48,4.6,3.2,1.4,0.2,Iris-setosa
-49,5.3,3.7,1.5,0.2,Iris-setosa
-50,5.0,3.3,1.4,0.2,Iris-setosa
-51,7.0,3.2,4.7,1.4,Iris-versicolor
-52,6.4,3.2,4.5,1.5,Iris-versicolor
-53,6.9,3.1,4.9,1.5,Iris-versicolor
-54,5.5,2.3,4.0,1.3,Iris-versicolor
-55,6.5,2.8,4.6,1.5,Iris-versicolor
-56,5.7,2.8,4.5,1.3,Iris-versicolor
-57,6.3,3.3,4.7,1.6,Iris-versicolor
-58,4.9,2.4,3.3,1.0,Iris-versicolor
-59,6.6,2.9,4.6,1.3,Iris-versicolor
-60,5.2,2.7,3.9,1.4,Iris-versicolor
-61,5.0,2.0,3.5,1.0,Iris-versicolor
-62,5.9,3.0,4.2,1.5,Iris-versicolor
-63,6.0,2.2,4.0,1.0,Iris-versicolor
-64,6.1,2.9,4.7,1.4,Iris-versicolor
-65,5.6,2.9,3.6,1.3,Iris-versicolor
-66,6.7,3.1,4.4,1.4,Iris-versicolor
-67,5.6,3.0,4.5,1.5,Iris-versicolor
-68,5.8,2.7,4.1,1.0,Iris-versicolor
-69,6.2,2.2,4.5,1.5,Iris-versicolor
-70,5.6,2.5,3.9,1.1,Iris-versicolor
-71,5.9,3.2,4.8,1.8,Iris-versicolor
-72,6.1,2.8,4.0,1.3,Iris-versicolor
-73,6.3,2.5,4.9,1.5,Iris-versicolor
-74,6.1,2.8,4.7,1.2,Iris-versicolor
-75,6.4,2.9,4.3,1.3,Iris-versicolor
-76,6.6,3.0,4.4,1.4,Iris-versicolor
-77,6.8,2.8,4.8,1.4,Iris-versicolor
-78,6.7,3.0,5.0,1.7,Iris-versicolor
-79,6.0,2.9,4.5,1.5,Iris-versicolor
-80,5.7,2.6,3.5,1.0,Iris-versicolor
-81,5.5,2.4,3.8,1.1,Iris-versicolor
-82,5.5,2.4,3.7,1.0,Iris-versicolor
-83,5.8,2.7,3.9,1.2,Iris-versicolor
-84,6.0,2.7,5.1,1.6,Iris-versicolor
-85,5.4,3.0,4.5,1.5,Iris-versicolor
-86,6.0,3.4,4.5,1.6,Iris-versicolor
-87,6.7,3.1,4.7,1.5,Iris-versicolor
-88,6.3,2.3,4.4,1.3,Iris-versicolor
-89,5.6,3.0,4.1,1.3,Iris-versicolor
-90,5.5,2.5,4.0,1.3,Iris-versicolor
-91,5.5,2.6,4.4,1.2,Iris-versicolor
-92,6.1,3.0,4.6,1.4,Iris-versicolor
-93,5.8,2.6,4.0,1.2,Iris-versicolor
-94,5.0,2.3,3.3,1.0,Iris-versicolor
-95,5.6,2.7,4.2,1.3,Iris-versicolor
-96,5.7,3.0,4.2,1.2,Iris-versicolor
-97,5.7,2.9,4.2,1.3,Iris-versicolor
-98,6.2,2.9,4.3,1.3,Iris-versicolor
-99,5.1,2.5,3.0,1.1,Iris-versicolor
-100,5.7,2.8,4.1,1.3,Iris-versicolor
-101,6.3,3.3,6.0,2.5,Iris-virginica
-102,5.8,2.7,5.1,1.9,Iris-virginica
-103,7.1,3.0,5.9,2.1,Iris-virginica
-104,6.3,2.9,5.6,1.8,Iris-virginica
-105,6.5,3.0,5.8,2.2,Iris-virginica
-106,7.6,3.0,6.6,2.1,Iris-virginica
-107,4.9,2.5,4.5,1.7,Iris-virginica
-108,7.3,2.9,6.3,1.8,Iris-virginica
-109,6.7,2.5,5.8,1.8,Iris-virginica
-110,7.2,3.6,6.1,2.5,Iris-virginica
-111,6.5,3.2,5.1,2.0,Iris-virginica
-112,6.4,2.7,5.3,1.9,Iris-virginica
-113,6.8,3.0,5.5,2.1,Iris-virginica
-114,5.7,2.5,5.0,2.0,Iris-virginica
-115,5.8,2.8,5.1,2.4,Iris-virginica
-116,6.4,3.2,5.3,2.3,Iris-virginica
-117,6.5,3.0,5.5,1.8,Iris-virginica
-118,7.7,3.8,6.7,2.2,Iris-virginica
-119,7.7,2.6,6.9,2.3,Iris-virginica
-120,6.0,2.2,5.0,1.5,Iris-virginica
-121,6.9,3.2,5.7,2.3,Iris-virginica
-122,5.6,2.8,4.9,2.0,Iris-virginica
-123,7.7,2.8,6.7,2.0,Iris-virginica
-124,6.3,2.7,4.9,1.8,Iris-virginica
-125,6.7,3.3,5.7,2.1,Iris-virginica
-126,7.2,3.2,6.0,1.8,Iris-virginica
-127,6.2,2.8,4.8,1.8,Iris-virginica
-128,6.1,3.0,4.9,1.8,Iris-virginica
-129,6.4,2.8,5.6,2.1,Iris-virginica
-130,7.2,3.0,5.8,1.6,Iris-virginica
-131,7.4,2.8,6.1,1.9,Iris-virginica
-132,7.9,3.8,6.4,2.0,Iris-virginica
-133,6.4,2.8,5.6,2.2,Iris-virginica
-134,6.3,2.8,5.1,1.5,Iris-virginica
-135,6.1,2.6,5.6,1.4,Iris-virginica
-136,7.7,3.0,6.1,2.3,Iris-virginica
-137,6.3,3.4,5.6,2.4,Iris-virginica
-138,6.4,3.1,5.5,1.8,Iris-virginica
-139,6.0,3.0,4.8,1.8,Iris-virginica
-140,6.9,3.1,5.4,2.1,Iris-virginica
-141,6.7,3.1,5.6,2.4,Iris-virginica
-142,6.9,3.1,5.1,2.3,Iris-virginica
-143,5.8,2.7,5.1,1.9,Iris-virginica
-144,6.8,3.2,5.9,2.3,Iris-virginica
-145,6.7,3.3,5.7,2.5,Iris-virginica
-146,6.7,3.0,5.2,2.3,Iris-virginica
-147,6.3,2.5,5.0,1.9,Iris-virginica
-148,6.5,3.0,5.2,2.0,Iris-virginica
-149,6.2,3.4,5.4,2.3,Iris-virginica
-150,5.9,3.0,5.1,1.8,Iris-virginica

README.md

@@ -1,31 +0,0 @@
----
-license: cc0-1.0
----
-## Iris Species Dataset
-
-The Iris dataset was used in R.A. Fisher's classic 1936 paper, The Use of Multiple Measurements in Taxonomic Problems, and can also be found on the UCI Machine Learning Repository.
-
-It includes three iris species with 50 samples each as well as some properties about each flower. One flower species is linearly separable from the other two, but the other two are not linearly separable from each other.
-The dataset is taken from [UCI Machine Learning Repository's Kaggle](https://www.kaggle.com/datasets/uciml/iris).
-The following description is taken from UCI Machine Learning Repository. 
-This is perhaps the best known database to be found in the pattern recognition literature. Fisher's paper is a classic in the field and is referenced frequently to this day. (See Duda & Hart, for example.) The data set contains 3 classes of 50 instances each, where each class refers to a type of iris plant. One class is linearly separable from the other 2; the latter are NOT linearly separable from each other.
-
-Predicted attribute: class of iris plant.
-
-This is an exceedingly simple domain.
-
-This data differs from the data presented in Fishers article (identified by Steve Chadwick, spchadwick '@' espeedaz.net ). The 35th sample should be: 4.9,3.1,1.5,0.2,"Iris-setosa" where the error is in the fourth feature. The 38th sample: 4.9,3.6,1.4,0.1,"Iris-setosa" where the errors are in the second and third features.
-
-
-Features in this dataset are the following:
-
-- sepal length in cm 
-- sepal width in cm
-- petal length in cm
-- petal width in cm
-- class:
-  - Iris Setosa
-  - Iris Versicolour
-  - Iris Virginica
-
-

scikit-learn--iris/csv-train.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:626e74e5a665eaa399a409c67ff8178318dbc59f7c49007af88b9b1fbc7fa20f
+size 5229