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.devel/sphinx/weave/suite-v1.Rmd

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@@ -11,7 +11,8 @@ def summarise_battery(battery):
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"~/Projects/clustering-data-v1/.catalogue/%s.csv" % battery
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)
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x = x.iloc[:, 1:] # skip battery
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x["g"] = np.round(x["g"], 2)
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x.loc[:, "g"] = np.round(x.loc[:, "g"], 2)
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x = x.astype(str)
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x = x.rename(columns=dict(
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noise="noise points",
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k="*k*",
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labels="reference labels",
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))
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x.iloc[:, 0] = x.iloc[:, 0].astype(str)
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x.iloc[:, 1] = x.iloc[:, 1].astype(str)
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x.iloc[:, 2] = x.iloc[:, 2].astype(str)
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idx = [""]*x.shape[0]
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j = 1
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for i in range(x.shape[0]):

.devel/sphinx/weave/suite-v1.md

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@@ -108,58 +108,6 @@ and
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Adam Wawrzeńczyk.
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Thanks!
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Name: *d*, dtype: object' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.
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| | dataset | *n* | *d* | reference labels | *k* | noise points | *g* |
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|:---|:-------------------|:------|:------|:-------------------|------:|---------------:|------:|
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| 1 | **circles** | 4000 | 2 | labels0 | 4 | 0 | 0 |
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We excluded the `DIM`-sets as they are too easy for most algorithms.
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Name: *d*, dtype: object' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.
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| | dataset | *n* | *d* | reference labels | *k* | noise points | *g* |
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| 1 | **a1** | 3000 | 2 | labels0 | 20 | 0 | 0 |
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[*FCPS*](https://CRAN.R-project.org/package=FCPS);
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see also {cite}`ThrunUltsch2020:fcps`.
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The dataset consist of 200–1050 observations in 2 dimensions.
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They came with no reference labels, so we had to create them ourselves.
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* `square` – a dataset of unknown/unconfirmed origin
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(🚧 help needed 🚧).
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problematic; due to their being high-dimensional, it is difficult
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Just like in the case of {ref}`sec:battery-g2mg`, we recommend
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| 1 | **h2mg_1_10** | 2048 | 1 | labels0 | 2 | 0 | 0 |

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