deploy: 55bca85

deck-options.html

@@ -191,7 +191,14 @@ <h1 id="deck-options"><a class="header" href="#deck-options">Deck Options</a></h
 <li><a href="#audio">Audio</a></li>
 <li><a href="#advanced">Advanced</a>
 <ul>
-<li><a href="#fsrs">FSRS</a></li>
+<li><a href="#fsrs">FSRS</a>
+<ul>
+<li><a href="#fsrs-options">FSRS Options</a></li>
+<li><a href="#learning-and-re-learning-steps">Learning and re-learning steps</a></li>
+<li><a href="#add-on-compatibility">Add-On Compatibility</a></li>
+<li><a href="#more">More</a></li>
+</ul>
+</li>
 <li><a href="#maximum-interval">Maximum Interval</a></li>
 <li><a href="#starting-ease">Starting Ease</a></li>
 <li><a href="#easy-bonus">Easy Bonus</a></li>
@@ -448,6 +455,10 @@ <h3 id="new-card-gather-order"><a class="header" href="#new-card-gather-order">N
 ways.</p>
 </li>
 <li>
+<p>Deck, then random notes: gathers cards from each deck in order, starting from the top.
+Cards from each deck are gathered randomly.</p>
+</li>
+<li>
 <p>Ascending position: gathers cards by ascending position (due #), which is typically the oldest-added first.</p>
 </li>
 <li>
@@ -553,9 +564,134 @@ <h3 id="fsrs"><a class="header" href="#fsrs">FSRS</a></h3>
 This setting is shared by all deck presets.</p>
 <p>FSRS is currently in the advanced section, as it was only just integrated into
 Anki in the 23.10 release. When you enable the setting, some new options will
-become available, and SM-2 specific settings will be hidden.</p>
-<p>If you previously used the 'custom scheduling' version of FSRS, please make
-sure you clear out the custom scheduling section before enabling FSRS.</p>
+become available, and SM-2 specific settings, such as &quot;Graduating interval&quot;,
+&quot;Easy bonus&quot;, etc, will be hidden.</p>
+<p><strong>Before Enabling</strong></p>
+<ul>
+<li>Please ensure all of your Anki clients support FSRS. Anki 23.10, AnkiMobile 23.10,
+and AnkiWeb all support it. AnkiDroid supports it in 2.17alpha3+. If
+one of your clients doesn't support it, things will not work correctly.</li>
+<li>If you previously used the 'custom scheduling' version of FSRS, please make
+sure you clear out the custom scheduling section before enabling FSRS.</li>
+</ul>
+<h4 id="fsrs-options"><a class="header" href="#fsrs-options">FSRS Options</a></h4>
+<p><strong>Desired Retention</strong></p>
+<p>Desired retention controls how likely you are to remember cards when they are reviewed.
+The default value of 0.9 will schedule cards so you have a 90% chance of remembering
+them when they come up for review again.</p>
+<p>Here is a graph that shows how adjusting this value will affect your workload:</p>
+<img src="media/FSRS_retention.png" width="600">
+<p>There are two things to notice:</p>
+<ul>
+<li>
+<p>As desired retention approaches 1.0, the frequency that you need to review cards
+increases drastically. For example, imagine you have a card that you have a 90%
+chance of remembering after 100 days. If your desired retention was 0.95, you'd
+need to review it after 47 days instead (approximately twice as frequently).
+At 0.97, the delay would be only 27 days (approximately 3.7x as frequently).
+At 0.99, you'd be reviewing every 9 days (more than 10x what you'd be doing with
+the defaults).</p>
+</li>
+<li>
+<p>As desired retention decreases, you'll forget a greater percentage of your
+cards, and those cards will need to be reviewed again. Eventually, you'll
+get to a point where the forgotten cards contribute more to your workload
+than you gain from the longer delays, which is why you see the workload
+on the left of the graph increasing. Also, bear in mind that forgetting
+material frequently is demotivating.</p>
+</li>
+</ul>
+<p>For these reasons, we suggest you be conservative when adjusting this
+number, and recommend you keep it between 0.85 and 0.95.</p>
+<p><strong>SM-2 retention</strong></p>
+<p>If your actual retention before switching to FSRS was significantly different
+from 0.9, adjusting this value will allow Anki to better estimate your memory
+state when it encounters cards that are missing review logs. Since review
+logs typically won't be missing unless you explicitly deleted them to free
+up space, most users will not need to adjust this.</p>
+<p><strong>FSRS parameters</strong></p>
+<p>FSRS parameters affect how cards are scheduled. They are not intended to be
+manually modified. Once you've accumulated 1000+ reviews, you can have Anki
+optimize the parameters for you, based on your review history.</p>
+<p><strong>Reschedule cards on change</strong></p>
+<p>This option controls whether the due dates of cards will be changed when you
+enable FSRS, or change the parameters. The default is not to reschedule
+cards: future reviews will use the new scheduling, but there will be no
+immediate change to your workload. If rescheduling is enabled, the due dates
+of cards will be changed, often resulting in a large number of cards becoming
+due, so <strong>activating this option is not recommended</strong> when first switching from SM2.</p>
+<p>If you wish to visualize how FSRS would change your schedule without altering
+your workload, there are two ways you can do so:</p>
+<ul>
+<li>Enable FSRS without rescheduling, and compare the interval and stability
+graphs. The interval graph will show the current intervals of cards; the stability
+graph will show the intervals FSRS would give cards if the desired retention is 0.9.</li>
+<li>Create a backup, enable FSRS with rescheduling, check the future due graph, and then
+undo or restore from the backup.</li>
+</ul>
+<p><strong>Optimize FSRS parameters</strong></p>
+<p>The FSRS optimizer uses machine learning to learn your memory patterns
+and find parameters that best fit your review history. So, the optimizer
+requires several reviews to fine-tune the parameters.</p>
+<p>If you have less than 1,000 reviews, you can use the default parameters that
+are already entered into the &quot;FSRS parameters&quot; field. Even with the default
+parameters, FSRS should work well for most users.</p>
+<p>Once you've done 1000+ reviews in Anki, you can use the Optimize button to
+analyze your review history, and automatically generate parameters that are
+optimal for your memory and the content you're studying. Parameters are
+preset-specific, so if you have decks that vary wildly in difficulty, it
+is recommended to assign them separate presets, as the parameters for easy
+decks and hard decks will be different. There is no need to optimize your
+parameters frequently - once every few months is sufficient.</p>
+<p>By default, parameters will be calculated from the review history of all
+decks using the current preset. You can optionally adjust the search
+before calculating the parameters, if you'd like to alter which cards
+are used for optimizing the parameters.</p>
+<p><strong>Evaluate FSRS parameters</strong></p>
+<p>You can use the Evaluate button in the &quot;Optimize FSRS parameters&quot;
+section to see metrics that show how well the parameters in the
+&quot;Model parameters&quot; field fit your review history. Smaller numbers
+indicate a better fit to your review history.</p>
+<p>Log-loss doesn't have an intuitive interpretation. RMSE (bins) can be
+interpreted as the average difference between the predicted probability
+of recalling a card (R) and the measured (from the review history)
+probability. For example, RMSE=5% means that, on average, FSRS
+is off by 5% when predicting R.</p>
+<p>Note that log-loss and RMSE (bins) are not perfectly correlated,
+so two decks may have similar RMSE values but very different log-loss values,
+and vice-versa.</p>
+<p><strong>Compute optimal retention</strong></p>
+<p>This experimental tool assumes you're starting with 0 cards, and will
+attempt to calculate the amount of material you'll be able to retain
+in the given time frame. The estimated retention will greatly depend
+on your inputs, and if it significantly differs from 0.9, it's a sign
+that the time you've allocated each day is either too low or too high
+for the amount of cards you're trying to learn. This number can be
+useful as a reference, but it is not recommended to copy it into the
+desired retention field.</p>
+<h4 id="learning-and-re-learning-steps"><a class="header" href="#learning-and-re-learning-steps">Learning and re-learning steps</a></h4>
+<p>(Re)learning steps of 1+ days are not recommended when using FSRS. The main
+reason they were popular with the old SM-2 scheduler is because repeatedly
+failing a card after learning could reduce its ease a lot, leading to what
+some people called &quot;ease hell&quot;. This is not a problem that FSRS suffers from.
+By keeping your learning steps under a day, you will allow FSRS to schedule
+cards at times it has calculated are optimum for your material and memory.
+Another reason not to use longer learning steps is because FSRS may end up
+scheduling the first review for a shorter time than your last learning step,
+leading to the Hard button showing a longer time than Good.</p>
+<p>We also recommend you keep the number of learning steps to a minimum. Evidence
+shows that repeating a card multiple times in a single day after you've
+remembered it does not significantly help with memory, so your time is
+better spent on other cards or a shorter study session</p>
+<h4 id="add-on-compatibility"><a class="header" href="#add-on-compatibility">Add-On Compatibility</a></h4>
+<p>Some add-ons can cause conflicts with FSRS. As a general rule of thumb,
+if an add-on affects a card's intervals, it shouldn't be used with FSRS.</p>
+<h4 id="more"><a class="header" href="#more">More</a></h4>
+<p>For more info on FSRS, please check:</p>
+<ul>
+<li><a href="https://github.com/open-spaced-repetition/fsrs4anki/wiki">FSRS4Anki Wiki</a></li>
+<li><a href="https://github.com/open-spaced-repetition/fsrs4anki">FSRS4Anki on Github</a></li>
+</ul>
 <h3 id="maximum-interval"><a class="header" href="#maximum-interval">Maximum Interval</a></h3>
 <p>Allows you to place an upper limit on the time Anki
 will wait to reshow a card. The default is 100 years; you can decrease